Specify curve as bn254

(1) C++ template API that is backend (GPU, ZPU or other) agnostic
(polynomials.h)
(2) concrete CUDA implementation (polynomial_cuda_backend.cu/cuh)
(3) C API for FFI
(4) Groth16 example (test)
(5) icicle library is now built for tests as well. Polynomial tests are
linked to icicle lib.

.github/workflows/codespell.yml

@@ -4,7 +4,7 @@ on:
   pull_request:
     branches:
       - main
-      - dev
+      - V2
 
 jobs:
   spelling-checker:

.github/workflows/cpp_cuda.yml

@@ -4,11 +4,11 @@ on:
   pull_request:
     branches:
       - main
-      - dev
+      - V2
   push:
     branches:
       - main
-      - dev
+      - V2
 
 concurrency:
   group: ${{ github.workflow }}-${{ github.ref }}
@@ -29,7 +29,7 @@ jobs:
       if: needs.check-changed-files.outputs.cpp_cuda == 'true'
       run: if [[ $(find ./ \( -path ./icicle/build -prune -o -path ./**/target -prune -o -path ./examples -prune \) -iname *.h -or -iname *.cuh -or -iname *.cu -or -iname *.c -or -iname *.cpp | xargs clang-format --dry-run -ferror-limit=1 -style=file 2>&1) ]]; then echo "Please run clang-format"; exit 1; fi
 
-  test-linux:
+  test-linux-curve:
     name: Test on Linux
     runs-on: [self-hosted, Linux, X64, icicle]
     needs: [check-changed-files, check-format]
@@ -39,14 +39,36 @@ jobs:
     steps:
     - name: Checkout Repo
       uses: actions/checkout@v4
-    - name: Build
+    - name: Build curve
       working-directory: ./icicle
       if: needs.check-changed-files.outputs.cpp_cuda == 'true'
       run: |
-        mkdir -p build
-        cmake -DBUILD_TESTS=ON -DCMAKE_BUILD_TYPE=Release -DCURVE=${{ matrix.curve }} -DG2_DEFINED=ON -S . -B build
-        cmake --build build
-    - name: Run C++ Tests
-      working-directory: ./icicle/build
+        mkdir -p build && rm -rf build/*
+        cmake -DCMAKE_BUILD_TYPE=Release -DBUILD_TESTS=ON -DCURVE=${{ matrix.curve }} -DG2=ON -S . -B build
+        cmake --build build -j
+    - name: Run C++ curve Tests
+      working-directory: ./icicle/build/tests
       if: needs.check-changed-files.outputs.cpp_cuda == 'true'
       run: ctest
+
+  test-linux-field:
+    name: Test on Linux
+    runs-on: [self-hosted, Linux, X64, icicle]
+    needs: [check-changed-files, check-format]
+    strategy:
+      matrix:
+        field: [babybear]
+    steps:
+    - name: Checkout Repo
+      uses: actions/checkout@v4
+    - name: Build field
+      working-directory: ./icicle
+      if: needs.check-changed-files.outputs.cpp_cuda == 'true'
+      run: |
+        mkdir -p build && rm -rf build/*
+        cmake -DCMAKE_BUILD_TYPE=Release -DBUILD_TESTS=ON -DFIELD=${{ matrix.field }} -DEXT_FIELD=ON -S . -B build
+        cmake --build build -j
+    - name: Run C++ field Tests
+      working-directory: ./icicle/build/tests
+      if: needs.check-changed-files.outputs.cpp_cuda == 'true'
+      run: ctest

.github/workflows/examples.yml

@@ -11,11 +11,11 @@ on:
   pull_request:
     branches:
       - main
-      - dev
+      - V2
   push:
     branches:
       - main
-      - dev
+      - V2
 
 concurrency:
   group: ${{ github.workflow }}-${{ github.ref }}

.github/workflows/golang.yml

@@ -4,11 +4,11 @@ on:
   pull_request:
     branches:
       - main
-      - dev
+      - V2
   push:
     branches:
       - main
-      - dev
+      - V2
 
 concurrency:
   group: ${{ github.workflow }}-${{ github.ref }}
@@ -50,13 +50,15 @@ jobs:
     - name: Build
       working-directory: ./wrappers/golang
       if: needs.check-changed-files.outputs.golang == 'true' || needs.check-changed-files.outputs.cpp_cuda == 'true'
-      run: ./build.sh ${{ matrix.curve }} ON ON # builds a single curve with G2 and ECNTT enabled
+      run: ./build.sh ${{ matrix.curve }} -g2 -ecntt # builds a single curve with G2 and ECNTT enabled
     - name: Upload ICICLE lib artifacts
       uses: actions/upload-artifact@v4
       if: needs.check-changed-files.outputs.golang == 'true' || needs.check-changed-files.outputs.cpp_cuda == 'true'
       with:
         name: icicle-builds-${{ matrix.curve }}-${{ github.workflow }}-${{ github.sha }}
-        path: icicle/build/libingo_${{ matrix.curve }}.a
+        path: |
+          icicle/build/src/curves/libingo_curve_${{ matrix.curve }}.a
+          icicle/build/src/fields/libingo_field_${{ matrix.curve }}.a
         retention-days: 1
   
   test-linux:
@@ -74,7 +76,7 @@ jobs:
       uses: actions/download-artifact@v4
       if: needs.check-changed-files.outputs.golang == 'true' || needs.check-changed-files.outputs.cpp_cuda == 'true'
       with:
-        path: ./icicle/build/
+        path: ./icicle/build/src
         merge-multiple: true
     - name: Run Tests
       working-directory: ./wrappers/golang

.github/workflows/rust.yml

@@ -4,11 +4,11 @@ on:
   pull_request:
     branches:
       - main
-      - dev
+      - V2
   push:
     branches:
       - main
-      - dev
+      - V2
 
 concurrency:
   group: ${{ github.workflow }}-${{ github.ref }}
@@ -60,7 +60,11 @@ jobs:
       if: needs.check-changed-files.outputs.rust == 'true' || needs.check-changed-files.outputs.cpp_cuda == 'true'
       # Running tests from the root workspace will run all workspace members' tests by default
       # We need to limit the number of threads to avoid running out of memory on weaker machines
-      run: cargo test --release --verbose --features=g2 -- --test-threads=2
+      run: cargo test --workspace --exclude icicle-babybear --release --verbose --features=g2 -- --test-threads=2
+    - name: Run baby bear tests
+      working-directory: ./wrappers/rust/icicle-fields/icicle-babybear
+      if: needs.check-changed-files.outputs.rust == 'true' || needs.check-changed-files.outputs.cpp_cuda == 'true'
+      run: cargo test --release --verbose
 
   build-windows:
     name: Build on Windows

.gitignore

@@ -16,6 +16,6 @@
 **/Cargo.lock
 **/icicle/build/
 **/wrappers/rust/icicle-cuda-runtime/src/bindings.rs
-**/build
+**/build*
 **/icicle/appUtils/large_ntt/work
 icicle/appUtils/large_ntt/work/test_ntt

README.md

@@ -115,8 +115,10 @@ This will ensure our custom hooks are run and will make it easier to follow our
 
 - [Robik](https://github.com/robik75), for his ongoing support and mentorship
 - [liuxiao](https://github.com/liuxiaobleach), for being a top notch bug smasher
-- [gkigiermo](https://github.com/gkigiermo), for making it intuitive to use ICICLE in Google Colab.
+- [gkigiermo](https://github.com/gkigiermo), for making it intuitive to use ICICLE in Google Colab
 - [nonam3e](https://github.com/nonam3e), for adding Grumpkin curve support into ICICLE
+- [alxiong](https://github.com/alxiong), for adding warmup for CudaStream
+- [cyl19970726](https://github.com/cyl19970726), for updating go install source in Dockerfile
 
 ## Help & Support
 

docs/docs/icicle/golang-bindings/msm-pre-computation.md

@@ -0,0 +1,92 @@
+# MSM Pre computation
+
+To understand the theory behind MSM pre computation technique refer to Niall Emmart's [talk](https://youtu.be/KAWlySN7Hm8?feature=shared&t=1734).
+
+### Supported curves
+
+`bls12-377`, `bls12-381`, `bn254`, `bw6-761`
+
+## Core package
+
+## MSM `PrecomputeBases`
+
+`PrecomputeBases` and `G2PrecomputeBases` exists for all supported curves. 
+
+#### Description
+
+This function extends each provided base point $(P)$ with its multiples $(2^lP, 2^{2l}P, ..., 2^{(precompute_factor - 1) \cdot l}P)$, where $(l)$ is a level of precomputation determined by the `precompute_factor`. The extended set of points facilitates faster MSM computations by allowing the MSM algorithm to leverage precomputed multiples of base points, reducing the number of point additions required during the computation.
+
+The precomputation process is crucial for optimizing MSM operations, especially when dealing with large sets of points and scalars. By precomputing and storing multiples of the base points, the MSM function can more efficiently compute the scalar-point multiplications.
+
+#### `PrecomputeBases`
+
+Precomputes bases for MSM by extending each base point with its multiples.
+
+```go
+func PrecomputeBases(points core.HostOrDeviceSlice, precomputeFactor int32, c int32, ctx *cr.DeviceContext, outputBases core.DeviceSlice) cr.CudaError
+```
+
+##### Parameters
+
+- **`points`**: A slice of the original affine points to be extended with their multiples.
+- **`precomputeFactor`**: Determines the total number of points to precompute for each base point.
+- **`c`**: Currently unused; reserved for future compatibility.
+- **`ctx`**: CUDA device context specifying the execution environment.
+- **`outputBases`**: The device slice allocated for storing the extended bases.
+
+##### Example
+
+```go
+cfg := GetDefaultMSMConfig()
+points := GenerateAffinePoints(1024)
+precomputeFactor := 8
+var precomputeOut core.DeviceSlice
+_, e := precomputeOut.Malloc(points[0].Size()*points.Len()*int(precomputeFactor), points[0].Size())
+
+err := PrecomputeBases(points, precomputeFactor, 0, &cfg.Ctx, precomputeOut)
+if err != cr.CudaSuccess {
+    log.Fatalf("PrecomputeBases failed: %v", err)
+}
+```
+
+#### `G2PrecomputeBases`
+
+This method is the same as `PrecomputeBases` but for G2 points. Extends each G2 curve base point with its multiples for optimized MSM computations.
+
+```go
+func G2PrecomputeBases(points core.HostOrDeviceSlice, precomputeFactor int32, c int32, ctx *cr.DeviceContext, outputBases core.DeviceSlice) cr.CudaError
+```
+
+##### Parameters
+
+- **`points`**: A slice of G2 curve points to be extended.
+- **`precomputeFactor`**: The total number of points to precompute for each base.
+- **`c`**: Reserved for future use to ensure compatibility with MSM operations.
+- **`ctx`**: Specifies the CUDA device context for execution.
+- **`outputBases`**: Allocated device slice for the extended bases.
+
+##### Example
+
+```go
+cfg := G2GetDefaultMSMConfig()
+points := G2GenerateAffinePoints(1024)
+precomputeFactor := 8
+var precomputeOut core.DeviceSlice
+_, e := precomputeOut.Malloc(points[0].Size()*points.Len()*int(precomputeFactor), points[0].Size())
+
+err := G2PrecomputeBases(points, precomputeFactor, 0, &cfg.Ctx, precomputeOut)
+if err != cr.CudaSuccess {
+    log.Fatalf("G2PrecomputeBases failed: %v", err)
+}
+```
+
+### Benchmarks
+
+Benchmarks where performed on a Nvidia RTX 3090Ti.
+
+| Pre-computation factor | bn254 size `2^20` MSM, ms.  | bn254 size `2^12` MSM, size `2^10` batch, ms. | bls12-381 size `2^20` MSM, ms. | bls12-381 size `2^12` MSM, size `2^10` batch, ms. |
+| ------------- | ------------- | ------------- | ------------- | ------------- |
+| 1  | 14.1  | 82.8  | 25.5  | 136.7  |
+| 2  | 11.8  | 76.6  | 20.3  | 123.8  |
+| 4  | 10.9  | 73.8  | 18.1  | 117.8  |
+| 8  | 10.6  | 73.7  | 17.2  | 116.0  |

docs/docs/icicle/golang-bindings/multi-gpu.md

@@ -0,0 +1,139 @@
+# Multi GPU APIs
+
+To learn more about the theory of Multi GPU programming refer to [this part](../multi-gpu.md) of documentation.
+
+Here we will cover the core multi GPU apis and a [example](#a-multi-gpu-example)
+
+
+## A Multi GPU example
+
+In this example we will display how you can
+
+1. Fetch the number of devices installed on a machine
+2. For every GPU launch a thread and set an active device per thread.
+3. Execute a MSM on each GPU
+
+
+```go
+func main() {
+	numDevices, _ := cuda_runtime.GetDeviceCount()
+	fmt.Println("There are ", numDevices, " devices available")
+	wg := sync.WaitGroup{}
+
+	for i := 0; i < numDevices; i++ {
+		wg.Add(1)
+        // RunOnDevice makes sure each MSM runs on a single thread
+		cuda_runtime.RunOnDevice(i, func(args ...any) {
+			defer wg.Done()
+			cfg := GetDefaultMSMConfig()
+			cfg.IsAsync = true
+			for _, power := range []int{10, 18} {
+				size := 1 << power // 2^pwr
+
+                // generate random scalars
+				scalars := GenerateScalars(size)
+				points := GenerateAffinePoints(size)
+
+                // create a stream and allocate result pointer
+				stream, _ := cuda_runtime.CreateStream()
+				var p Projective
+				var out core.DeviceSlice
+				_, e := out.MallocAsync(p.Size(), p.Size(), stream)
+                // assign stream to device context
+				cfg.Ctx.Stream = &stream
+
+                // execute MSM
+				e = Msm(scalars, points, &cfg, out)
+                // read result from device
+				outHost := make(core.HostSlice[Projective], 1)
+				outHost.CopyFromDeviceAsync(&out, stream)
+				out.FreeAsync(stream)
+
+                // sync the stream
+				cr.SynchronizeStream(&stream)
+			}
+		})
+	}
+	wg.Wait()
+}
+```
+
+This example demonstrates a basic pattern for distributing tasks across multiple GPUs. The `RunOnDevice` function ensures that each goroutine is executed on its designated GPU and a corresponding thread.
+
+## Device Management API
+
+To streamline device management we offer as part of `cuda_runtime` package methods for dealing with devices.
+
+### `RunOnDevice`
+
+Runs a given function on a specific GPU device, ensuring that all CUDA calls within the function are executed on the selected device.
+
+In Go, most concurrency can be done via Goroutines. However, there is no guarantee that a goroutine stays on a specific host thread. 
+
+`RunOnDevice` was designed to solve this caveat and insure that the goroutine will stay on a specific host thread.
+
+`RunOnDevice` will lock a goroutine into a specific host thread, sets a current GPU device, runs a provided function, and unlocks the goroutine from the host thread after the provided function finishes.
+
+While the goroutine is locked to the host thread, the Go runtime will not assign other goroutine's to that host thread.
+
+**Parameters:**
+
+- `deviceId int`: The ID of the device on which to run the provided function. Device IDs start from 0.
+- `funcToRun func(args ...any)`: The function to be executed on the specified device.
+- `args ...any`: Arguments to be passed to `funcToRun`.
+
+**Behavior:**
+
+- The function `funcToRun` is executed in a new goroutine that is locked to a specific OS thread to ensure that all CUDA calls within the function target the specified device.
+- It's important to note that any goroutines launched within `funcToRun` are not automatically bound to the same GPU device. If necessary, `RunOnDevice` should be called again within such goroutines with the same `deviceId`.
+
+**Example:**
+
+```go
+RunOnDevice(0, func(args ...any) {
+	fmt.Println("This runs on GPU 0")
+	// CUDA-related operations here will target GPU 0
+}, nil)
+```
+
+### `SetDevice`
+
+Sets the active device for the current host thread. All subsequent CUDA calls made from this thread will target the specified device.
+
+**Parameters:**
+
+- `device int`: The ID of the device to set as the current device.
+
+**Returns:**
+
+- `CudaError`: Error code indicating the success or failure of the operation.
+
+### `GetDeviceCount`
+
+Retrieves the number of CUDA-capable devices available on the host.
+
+**Returns:**
+
+- `(int, CudaError)`: The number of devices and an error code indicating the success or failure of the operation.
+
+### `GetDevice`
+
+Gets the ID of the currently active device for the calling host thread.
+
+**Returns:**
+
+- `(int, CudaError)`: The ID of the current device and an error code indicating the success or failure of the operation.
+
+### `GetDeviceFromPointer`
+
+Retrieves the device associated with a given pointer.
+
+**Parameters:**
+
+- `ptr unsafe.Pointer`: Pointer to query.
+
+**Returns:**
+
+- `int`: The device ID associated with the memory pointed to by `ptr`.
+
+This documentation should provide a clear understanding of how to effectively manage multiple GPUs in Go applications using CUDA, with a particular emphasis on the `RunOnDevice` function for executing tasks on specific GPUs.

docs/docs/icicle/golang-bindings/ntt.md

@@ -64,10 +64,12 @@ type NTTConfig[T any] struct {
     Ctx cr.DeviceContext
     CosetGen T
     BatchSize int32
+    ColumnsBatch bool
     Ordering Ordering
     areInputsOnDevice  bool
     areOutputsOnDevice bool
     IsAsync bool
+    NttAlgorithm NttAlgorithm
 }
 ```
 
@@ -76,10 +78,12 @@ type NTTConfig[T any] struct {
 - **Ctx**: Device context containing details like device ID and stream ID.
 - **CosetGen**: Coset generator used for coset (i)NTTs, defaulting to no coset being used.
 - **BatchSize**: The number of NTTs to compute in one operation, defaulting to 1.
+- **ColumnsBatch**: If true the function will compute the NTTs over the columns of the input matrix and not over the rows. Defaults to `false`.
 - **Ordering**: Ordering of inputs and outputs (`KNN`, `KNR`, `KRN`, `KRR`, `KMN`, `KNM`), affecting how data is arranged.
 - **areInputsOnDevice**: Indicates if input scalars are located on the device.
 - **areOutputsOnDevice**: Indicates if results are stored on the device.
 - **IsAsync**: Controls whether the NTT operation runs asynchronously.
+- **NttAlgorithm**: Explicitly select the NTT algorithm. Default value: Auto (the implementation selects radix-2 or mixed-radix algorithm based on heuristics).
 
 ### Default Configuration
 

docs/docs/icicle/polynomials/ffi.uml

@@ -0,0 +1,27 @@
+@startuml
+skinparam componentStyle uml2
+
+' Define Components
+component "C++ Template\nComponent" as CppTemplate {
+  [Parameterizable Interface]
+}
+component "C API Wrapper\nComponent" as CApiWrapper {
+  [C API Interface]
+}
+component "Rust Code\nComponent" as RustCode {
+  [Macro Interface\n(Template Instantiation)]
+}
+
+' Define Artifact
+artifact "Static Library\n«artifact»" as StaticLib
+
+' Connections
+CppTemplate -down-> CApiWrapper : Instantiates
+CApiWrapper .down.> StaticLib : Compiles into
+RustCode -left-> StaticLib : Links against\nand calls via FFI
+
+' Notes
+note right of CppTemplate : Generic C++\ntemplate implementation
+note right of CApiWrapper : Exposes C API for FFI\nto Rust/Go
+note right of RustCode : Uses macros to\ninstantiate templates
+@enduml

docs/docs/icicle/polynomials/hw_backends.uml

@@ -0,0 +1,86 @@
+@startuml
+
+' Define Interface for Polynomial Backend Operations
+interface IPolynomialBackend {
+    +add()
+    +subtract()
+    +multiply()
+    +divide()
+    +evaluate()
+}
+
+' Define Interface for Polynomial Context (State Management)
+interface IPolynomialContext {
+    +initFromCoeffs()
+    +initFromEvals()
+    +getCoeffs()
+    +getEvals()
+}
+
+' PolynomialAPI now uses two strategies: Backend and Context
+class PolynomialAPI {
+    -backendStrategy: IPolynomialBackend
+    -contextStrategy: IPolynomialContext
+    -setBackendStrategy(IPolynomialBackend)
+    -setContextStrategy(IPolynomialContext)
+    +add()
+    +subtract()
+    +multiply()
+    +divide()
+    +evaluate()
+}
+
+' Backend Implementations
+class GPUPolynomialBackend implements IPolynomialBackend {
+    #gpuResources: Resource
+    +add()
+    +subtract()
+    +multiply()
+    +divide()
+    +evaluate()
+}
+
+class ZPUPolynomialBackend implements IPolynomialBackend {
+    #zpuResources: Resource
+    +add()
+    +subtract()
+    +multiply()
+    +divide()
+    +evaluate()
+}
+
+class TracerPolynomialBackend implements IPolynomialBackend {
+    #traceData: Data
+    +add()
+    +subtract()
+    +multiply()
+    +divide()
+    +evaluate()
+}
+
+' Context Implementations (Placeholder for actual implementation)
+class GPUContext implements IPolynomialContext {
+    +initFromCoeffs()
+    +initFromEvals()
+    +getCoeffs()
+    +getEvals()
+}
+
+class ZPUContext implements IPolynomialContext {
+    +initFromCoeffs()
+    +initFromEvals()
+    +getCoeffs()
+    +getEvals()
+}
+
+class TracerContext implements IPolynomialContext {
+    +initFromCoeffs()
+    +initFromEvals()
+    +getCoeffs()
+    +getEvals()
+}
+
+' Relationships
+PolynomialAPI o-- IPolynomialBackend : uses
+PolynomialAPI o-- IPolynomialContext : uses
+@enduml

docs/docs/icicle/rust-bindings/msm-pre-computation.md

@@ -0,0 +1,63 @@
+# MSM Pre computation
+
+To understand the theory behind MSM pre computation technique refer to Niall Emmart's [talk](https://youtu.be/KAWlySN7Hm8?feature=shared&t=1734).
+
+### Supported curves
+
+`bls12-377`, `bls12-381`, `bn254`, `bw6-761`, `Grumpkin`
+
+### `precompute_bases`
+
+Precomputes bases for the multi-scalar multiplication (MSM) by extending each base point with its multiples, facilitating more efficient MSM calculations.
+
+```rust
+pub fn precompute_bases<C: Curve + MSM<C>>(
+    points: &HostOrDeviceSlice<Affine<C>>,
+    precompute_factor: i32,
+    _c: i32,
+    ctx: &DeviceContext,
+    output_bases: &mut HostOrDeviceSlice<Affine<C>>,
+) -> IcicleResult<()>
+```
+
+
+#### Parameters
+
+- **`points`**: The original set of affine points (\(P_1, P_2, ..., P_n\)) to be used in the MSM. For batch MSM operations, this should include all unique points concatenated together.
+- **`precompute_factor`**: Specifies the total number of points to precompute for each base, including the base point itself. This parameter directly influences the memory requirements and the potential speedup of the MSM operation.
+- **`_c`**: Currently unused. Intended for future use to align with the `c` parameter in `MSMConfig`, ensuring the precomputation is compatible with the bucket method's window size used in MSM.
+- **`ctx`**: The device context specifying the device ID and stream for execution. This context determines where the precomputation is performed (e.g., on a specific GPU).
+- **`output_bases`**: The output buffer for the extended bases. Its size must be `points.len() * precompute_factor`. This buffer should be allocated on the device for GPU computations.
+
+#### Returns
+
+`Ok(())` if the operation is successful, or an `IcicleResult` error otherwise.
+
+#### Description
+
+This function extends each provided base point $(P)$ with its multiples $(2^lP, 2^{2l}P, ..., 2^{(precompute_factor - 1) \cdot l}P)$, where $(l)$ is a level of precomputation determined by the `precompute_factor`. The extended set of points facilitates faster MSM computations by allowing the MSM algorithm to leverage precomputed multiples of base points, reducing the number of point additions required during the computation.
+
+The precomputation process is crucial for optimizing MSM operations, especially when dealing with large sets of points and scalars. By precomputing and storing multiples of the base points, the MSM function can more efficiently compute the scalar-point multiplications.
+
+#### Example Usage
+
+```rust
+let device_context = DeviceContext::default_for_device(0); // Use the default device
+let precompute_factor = 4; // Number of points to precompute
+let mut extended_bases = HostOrDeviceSlice::cuda_malloc(expected_size).expect("Failed to allocate memory for extended bases");
+
+// Precompute the bases using the specified factor
+precompute_bases(&points, precompute_factor, 0, &device_context, &mut extended_bases)
+    .expect("Failed to precompute bases");
+```
+
+### Benchmarks
+
+Benchmarks where performed on a Nvidia RTX 3090Ti.
+
+| Pre-computation factor | bn254 size `2^20` MSM, ms.  | bn254 size `2^12` MSM, size `2^10` batch, ms. | bls12-381 size `2^20` MSM, ms. | bls12-381 size `2^12` MSM, size `2^10` batch, ms. |
+| ------------- | ------------- | ------------- | ------------- | ------------- |
+| 1  | 14.1  | 82.8  | 25.5  | 136.7  |
+| 2  | 11.8  | 76.6  | 20.3  | 123.8  |
+| 4  | 10.9  | 73.8  | 18.1  | 117.8  |
+| 8  | 10.6  | 73.7  | 17.2  | 116.0  |

docs/docs/icicle/rust-bindings/ntt.md

@@ -76,6 +76,7 @@ pub struct NTTConfig<'a, S> {
     pub ctx: DeviceContext<'a>,
     pub coset_gen: S,
     pub batch_size: i32,
+    pub columns_batch: bool,
     pub ordering: Ordering,
     are_inputs_on_device: bool,    
     are_outputs_on_device: bool,
@@ -94,6 +95,8 @@ The `NTTConfig` struct is a configuration object used to specify parameters for
 
 - **`batch_size: i32`**: Determines the number of NTTs to compute in a single batch. The default value is 1, meaning that operations are performed on individual inputs without batching. Batch processing can significantly improve performance by leveraging parallelism in GPU computations.
 
+- **`columns_batch`**: If true the function will compute the NTTs over the columns of the input matrix and not over the rows. Defaults to `false`.
+
 - **`ordering: Ordering`**: Controls the ordering of inputs and outputs for the NTT operation. This field can be used to specify decimation strategies (in time or in frequency) and the type of butterfly algorithm (Cooley-Tukey or Gentleman-Sande). The ordering is crucial for compatibility with various algorithmic approaches and can impact the efficiency of the NTT.
 
 - **`are_inputs_on_device: bool`**: Indicates whether the input data has been preloaded on the device memory. If `false` inputs will be copied from host to device.
@@ -122,6 +125,7 @@ let custom_config = NTTConfig {
     ctx: custom_device_context,
     coset_gen: my_coset_generator,
     batch_size: 10,
+    columns_batch: false,
     ordering: Ordering::kRN,
     are_inputs_on_device: true,
     are_outputs_on_device: true,

docs/sidebars.js

@@ -34,9 +34,20 @@ module.exports = {
           collapsed: true,
           items: [
             {
-              type: "doc",
+              type: "category",
               label: "MSM",
-              id: "icicle/golang-bindings/msm",
+              link: {
+                type: `doc`,
+                id: "icicle/golang-bindings/msm",
+              },
+              collapsed: true,
+              items: [
+                {
+                  type: "doc",
+                  label: "MSM pre computation",
+                  id: "icicle/golang-bindings/msm-pre-computation",
+                }
+              ]
             },
             {
               type: "doc",
@@ -48,6 +59,11 @@ module.exports = {
               label: "Vector operations",
               id: "icicle/golang-bindings/vec-ops",
             },
+            {
+            type: "doc",
+            label: "Multi GPU Support",
+            id: "icicle/golang-bindings/multi-gpu",
+            },
           ]
         },
         {
@@ -60,9 +76,20 @@ module.exports = {
           collapsed: true,
           items: [
             {
-              type: "doc",
+              type: "category",
               label: "MSM",
-              id: "icicle/rust-bindings/msm",
+              link: {
+                type: `doc`,
+                id: "icicle/rust-bindings/msm",
+              },
+              collapsed: true,
+              items: [
+                {
+                  type: "doc",
+                  label: "MSM pre computation",
+                  id: "icicle/rust-bindings/msm-pre-computation",
+                }
+              ]
             },
             {
               type: "doc",

examples/c++/polynomial_multiplication/example.cu

@@ -84,16 +84,14 @@ int main(int argc, char** argv)
 
       // (4) multiply A,B
       CHK_IF_RETURN(cudaMallocAsync(&MulGpu, sizeof(test_data) * NTT_SIZE, ntt_config.ctx.stream));
-      vec_ops::VecOpsConfig<test_data> config {
+      vec_ops::VecOpsConfig<test_data> config{
         ntt_config.ctx,
         true,  // is_a_on_device
         true,  // is_b_on_device
         true,  // is_result_on_device
-        false, // is_montgomery
         false  // is_async
       };
-      CHK_IF_RETURN(
-        vec_ops::Mul(GpuA, GpuB, NTT_SIZE, config, MulGpu));
+      CHK_IF_RETURN(vec_ops::Mul(GpuA, GpuB, NTT_SIZE, config, MulGpu));
 
       // (5) INTT (in place)
       ntt_config.are_inputs_on_device = true;
@@ -118,6 +116,7 @@ int main(int argc, char** argv)
   benchmark(false); // warmup
   benchmark(true, 20);
 
+  ntt::ReleaseDomain<test_scalar>(ntt_config.ctx);
   CHK_IF_RETURN(cudaStreamSynchronize(ntt_config.ctx.stream));
 
   return 0;

examples/rust/msm/Cargo.toml

@@ -8,12 +8,11 @@ icicle-cuda-runtime = { path = "../../../wrappers/rust/icicle-cuda-runtime" }
 icicle-core = { path = "../../../wrappers/rust/icicle-core" }
 icicle-bn254 = { path = "../../../wrappers/rust/icicle-curves/icicle-bn254", features = ["g2"] }
 icicle-bls12-377 = { path = "../../../wrappers/rust/icicle-curves/icicle-bls12-377" }
-ark-bn254 = { version = "0.4.0", optional = true}
-ark-bls12-377 = { version = "0.4.0", optional = true}
-ark-ec = { version = "0.4.0", optional = true}
+ark-bn254 = { version = "0.4.0", optional = true }
+ark-bls12-377 = { version = "0.4.0", optional = true }
+ark-ec = { version = "0.4.0", optional = true }
 clap = { version = "<=4.4.12", features = ["derive"] }
 
 [features]
 arkworks = ["ark-bn254", "ark-bls12-377", "ark-ec", "icicle-core/arkworks", "icicle-bn254/arkworks", "icicle-bls12-377/arkworks"]
 profile = []
-g2 = []

examples/rust/msm/src/main.rs

@@ -4,7 +4,10 @@ use icicle_bls12_377::curve::{
     CurveCfg as BLS12377CurveCfg, G1Projective as BLS12377G1Projective, ScalarCfg as BLS12377ScalarCfg,
 };
 
-use icicle_cuda_runtime::{memory::HostOrDeviceSlice, stream::CudaStream};
+use icicle_cuda_runtime::{
+    memory::{DeviceVec, HostSlice},
+    stream::CudaStream,
+};
 
 use icicle_core::{curve::Curve, msm, traits::GenerateRandom};
 
@@ -57,18 +60,18 @@ fn main() {
             log_size, size
         );
         // Setting Bn254 points and scalars
-        let points = HostOrDeviceSlice::Host(upper_points[..size].to_vec());
-        let g2_points = HostOrDeviceSlice::Host(g2_upper_points[..size].to_vec());
-        let scalars = HostOrDeviceSlice::Host(upper_scalars[..size].to_vec());
+        let points = HostSlice::from_slice(&upper_points[..size]);
+        let g2_points = HostSlice::from_slice(&g2_upper_points[..size]);
+        let scalars = HostSlice::from_slice(&upper_scalars[..size]);
 
         // Setting bls12377 points and scalars
         // let points_bls12377 = &upper_points_bls12377[..size];
-        let points_bls12377 = HostOrDeviceSlice::Host(upper_points_bls12377[..size].to_vec()); //  &upper_points_bls12377[..size];
-        let scalars_bls12377 = HostOrDeviceSlice::Host(upper_scalars_bls12377[..size].to_vec());
+        let points_bls12377 = HostSlice::from_slice(&upper_points_bls12377[..size]); //  &upper_points_bls12377[..size];
+        let scalars_bls12377 = HostSlice::from_slice(&upper_scalars_bls12377[..size]);
 
         println!("Configuring bn254 MSM...");
-        let mut msm_results: HostOrDeviceSlice<'_, G1Projective> = HostOrDeviceSlice::cuda_malloc(1).unwrap();
-        let mut g2_msm_results: HostOrDeviceSlice<'_, G2Projective> = HostOrDeviceSlice::cuda_malloc(1).unwrap();
+        let mut msm_results = DeviceVec::<G1Projective>::cuda_malloc(1).unwrap();
+        let mut g2_msm_results = DeviceVec::<G2Projective>::cuda_malloc(1).unwrap();
         let stream = CudaStream::create().unwrap();
         let g2_stream = CudaStream::create().unwrap();
         let mut cfg = msm::MSMConfig::default();
@@ -82,8 +85,7 @@ fn main() {
         g2_cfg.is_async = true;
 
         println!("Configuring bls12377 MSM...");
-        let mut msm_results_bls12377: HostOrDeviceSlice<'_, BLS12377G1Projective> =
-            HostOrDeviceSlice::cuda_malloc(1).unwrap();
+        let mut msm_results_bls12377 = DeviceVec::<BLS12377G1Projective>::cuda_malloc(1).unwrap();
         let stream_bls12377 = CudaStream::create().unwrap();
         let mut cfg_bls12377 = msm::MSMConfig::default();
         cfg_bls12377
@@ -94,7 +96,7 @@ fn main() {
         println!("Executing bn254 MSM on device...");
         #[cfg(feature = "profile")]
         let start = Instant::now();
-        msm::msm(&scalars, &points, &cfg, &mut msm_results).unwrap();
+        msm::msm(scalars, points, &cfg, &mut msm_results[..]).unwrap();
         #[cfg(feature = "profile")]
         println!(
             "ICICLE BN254 MSM on size 2^{log_size} took: {} ms",
@@ -102,16 +104,16 @@ fn main() {
                 .elapsed()
                 .as_millis()
         );
-        msm::msm(&scalars, &g2_points, &g2_cfg, &mut g2_msm_results).unwrap();
+        msm::msm(scalars, g2_points, &g2_cfg, &mut g2_msm_results[..]).unwrap();
 
         println!("Executing bls12377 MSM on device...");
         #[cfg(feature = "profile")]
         let start = Instant::now();
         msm::msm(
-            &scalars_bls12377,
-            &points_bls12377,
+            scalars_bls12377,
+            points_bls12377,
             &cfg_bls12377,
-            &mut msm_results_bls12377,
+            &mut msm_results_bls12377[..],
         )
         .unwrap();
         #[cfg(feature = "profile")]
@@ -134,10 +136,10 @@ fn main() {
             .synchronize()
             .unwrap();
         msm_results
-            .copy_to_host(&mut msm_host_result[..])
+            .copy_to_host(HostSlice::from_mut_slice(&mut msm_host_result[..]))
             .unwrap();
         g2_msm_results
-            .copy_to_host(&mut g2_msm_host_result[..])
+            .copy_to_host(HostSlice::from_mut_slice(&mut g2_msm_host_result[..]))
             .unwrap();
         println!("bn254 result: {:#?}", msm_host_result);
         println!("G2 bn254 result: {:#?}", g2_msm_host_result);
@@ -146,7 +148,7 @@ fn main() {
             .synchronize()
             .unwrap();
         msm_results_bls12377
-            .copy_to_host(&mut msm_host_result_bls12377[..])
+            .copy_to_host(HostSlice::from_mut_slice(&mut msm_host_result_bls12377[..]))
             .unwrap();
         println!("bls12377 result: {:#?}", msm_host_result_bls12377);
 
@@ -154,23 +156,19 @@ fn main() {
         {
             println!("Checking against arkworks...");
             let ark_points: Vec<Bn254G1Affine> = points
-                .as_slice()
                 .iter()
                 .map(|&point| point.to_ark())
                 .collect();
             let ark_scalars: Vec<Bn254Fr> = scalars
-                .as_slice()
                 .iter()
                 .map(|scalar| scalar.to_ark())
                 .collect();
 
             let ark_points_bls12377: Vec<Bls12377G1Affine> = points_bls12377
-                .as_slice()
                 .iter()
                 .map(|point| point.to_ark())
                 .collect();
             let ark_scalars_bls12377: Vec<Bls12377Fr> = scalars_bls12377
-                .as_slice()
                 .iter()
                 .map(|scalar| scalar.to_ark())
                 .collect();

examples/rust/ntt/src/main.rs

@@ -2,7 +2,11 @@ use icicle_bn254::curve::{ScalarCfg, ScalarField};
 
 use icicle_bls12_377::curve::{ScalarCfg as BLS12377ScalarCfg, ScalarField as BLS12377ScalarField};
 
-use icicle_cuda_runtime::{device_context::DeviceContext, memory::HostOrDeviceSlice, stream::CudaStream};
+use icicle_cuda_runtime::{
+    device_context::DeviceContext,
+    memory::{DeviceVec, HostSlice},
+    stream::CudaStream,
+};
 
 use icicle_core::{
     ntt::{self, NTT},
@@ -41,14 +45,13 @@ fn main() {
     );
     // Setting Bn254 points and scalars
     println!("Generating random inputs on host for bn254...");
-    let scalars = HostOrDeviceSlice::Host(ScalarCfg::generate_random(size));
-    let mut ntt_results: HostOrDeviceSlice<'_, ScalarField> = HostOrDeviceSlice::cuda_malloc(size).unwrap();
+    let scalars = ScalarCfg::generate_random(size);
+    let mut ntt_results = DeviceVec::<ScalarField>::cuda_malloc(size).unwrap();
 
     // Setting bls12377 points and scalars
     println!("Generating random inputs on host for bls12377...");
-    let scalars_bls12377 = HostOrDeviceSlice::Host(BLS12377ScalarCfg::generate_random(size));
-    let mut ntt_results_bls12377: HostOrDeviceSlice<'_, BLS12377ScalarField> =
-        HostOrDeviceSlice::cuda_malloc(size).unwrap();
+    let scalars_bls12377 = BLS12377ScalarCfg::generate_random(size);
+    let mut ntt_results_bls12377 = DeviceVec::<BLS12377ScalarField>::cuda_malloc(size).unwrap();
 
     println!("Setting up bn254 Domain...");
     let icicle_omega = <Bn254Fr as FftField>::get_root_of_unity(
@@ -86,7 +89,13 @@ fn main() {
     println!("Executing bn254 NTT on device...");
     #[cfg(feature = "profile")]
     let start = Instant::now();
-    ntt::ntt(&scalars, ntt::NTTDir::kForward, &cfg, &mut ntt_results).unwrap();
+    ntt::ntt(
+        HostSlice::from_slice(&scalars),
+        ntt::NTTDir::kForward,
+        &cfg,
+        &mut ntt_results[..],
+    )
+    .unwrap();
     #[cfg(feature = "profile")]
     println!(
         "ICICLE BN254 NTT on size 2^{log_size} took: {} μs",
@@ -99,10 +108,10 @@ fn main() {
     #[cfg(feature = "profile")]
     let start = Instant::now();
     ntt::ntt(
-        &scalars_bls12377,
+        HostSlice::from_slice(&scalars_bls12377),
         ntt::NTTDir::kForward,
         &cfg_bls12377,
-        &mut ntt_results_bls12377,
+        &mut ntt_results_bls12377[..],
     )
     .unwrap();
     #[cfg(feature = "profile")]
@@ -119,7 +128,7 @@ fn main() {
         .unwrap();
     let mut host_bn254_results = vec![ScalarField::zero(); size];
     ntt_results
-        .copy_to_host(&mut host_bn254_results[..])
+        .copy_to_host(HostSlice::from_mut_slice(&mut host_bn254_results[..]))
         .unwrap();
 
     stream_bls12377
@@ -127,19 +136,17 @@ fn main() {
         .unwrap();
     let mut host_bls12377_results = vec![BLS12377ScalarField::zero(); size];
     ntt_results_bls12377
-        .copy_to_host(&mut host_bls12377_results[..])
+        .copy_to_host(HostSlice::from_mut_slice(&mut host_bls12377_results[..]))
         .unwrap();
 
     println!("Checking against arkworks...");
     let mut ark_scalars: Vec<Bn254Fr> = scalars
-        .as_slice()
         .iter()
         .map(|scalar| scalar.to_ark())
         .collect();
     let bn254_domain = <Radix2EvaluationDomain<Bn254Fr> as EvaluationDomain<Bn254Fr>>::new(size).unwrap();
 
     let mut ark_scalars_bls12377: Vec<Bls12377Fr> = scalars_bls12377
-        .as_slice()
         .iter()
         .map(|scalar| scalar.to_ark())
         .collect();

examples/rust/poseidon/src/main.rs

@@ -4,7 +4,7 @@ use icicle_cuda_runtime::device_context::DeviceContext;
 
 use icicle_core::poseidon::{load_optimized_poseidon_constants, poseidon_hash_many, PoseidonConfig};
 use icicle_core::traits::FieldImpl;
-use icicle_cuda_runtime::memory::HostOrDeviceSlice;
+use icicle_cuda_runtime::memory::HostSlice;
 
 #[cfg(feature = "profile")]
 use std::time::Instant;
@@ -25,23 +25,29 @@ fn main() {
 
     println!("Running Icicle Examples: Rust Poseidon Hash");
     let arity = 2u32;
-    println!("---------------------- Loading optimized Poseidon constants for arity={} ------------------------", arity);
+    println!(
+        "---------------------- Loading optimized Poseidon constants for arity={} ------------------------",
+        arity
+    );
     let ctx = DeviceContext::default();
     let constants = load_optimized_poseidon_constants::<F>(arity, &ctx).unwrap();
     let config = PoseidonConfig::default();
 
-    println!("---------------------- Input size 2^{}={} ------------------------", size, test_size);
-    let inputs = vec![F::one(); test_size * arity as usize];
-    let outputs = vec![F::zero(); test_size];
-    let mut input_slice = HostOrDeviceSlice::on_host(inputs);
-    let mut output_slice = HostOrDeviceSlice::on_host(outputs);
+    println!(
+        "---------------------- Input size 2^{}={} ------------------------",
+        size, test_size
+    );
+    let mut inputs = vec![F::one(); test_size * arity as usize];
+    let mut outputs = vec![F::zero(); test_size];
+    let input_slice = HostSlice::from_mut_slice(&mut inputs);
+    let output_slice = HostSlice::from_mut_slice(&mut outputs);
 
     println!("Executing BLS12-381 Poseidon Hash on device...");
     #[cfg(feature = "profile")]
     let start = Instant::now();
     poseidon_hash_many::<F>(
-        &mut input_slice,
-        &mut output_slice,
+        input_slice,
+        output_slice,
         test_size as u32,
         arity as u32,
         &constants,
@@ -49,5 +55,10 @@ fn main() {
     )
     .unwrap();
     #[cfg(feature = "profile")]
-    println!("ICICLE BLS12-381 Poseidon Hash on size 2^{size} took: {} μs", start.elapsed().as_micros());
-}
+    println!(
+        "ICICLE BLS12-381 Poseidon Hash on size 2^{size} took: {} μs",
+        start
+            .elapsed()
+            .as_micros()
+    );
+}

icicle/CMakeLists.txt

@@ -1,165 +1,59 @@
 cmake_minimum_required(VERSION 3.18)
 
-# GoogleTest requires at least C++14
-set(CMAKE_CXX_STANDARD 17)
-set(CMAKE_CUDA_STANDARD 17)
-set(CMAKE_CUDA_STANDARD_REQUIRED TRUE)
-set(CMAKE_CXX_STANDARD_REQUIRED TRUE)
-
-if("$ENV{ICICLE_PIC}" STREQUAL "OFF" OR ICICLE_PIC STREQUAL "OFF")
-  message(WARNING "Note that PIC (position-independent code) is disabled.")
-else()
-  set(CMAKE_POSITION_INDEPENDENT_CODE ON)
-endif()
-
-# add the target cuda architectures
-# each additional architecture increases the compilation time and output file size
-if(${CMAKE_VERSION} VERSION_LESS "3.24.0")
-  set(CMAKE_CUDA_ARCHITECTURES ${CUDA_ARCH})
-else()
-  find_program(_nvidia_smi "nvidia-smi")
-
-  if(_nvidia_smi)
-    set(DETECT_GPU_COUNT_NVIDIA_SMI 0)
-
-    # execute nvidia-smi -L to get a short list of GPUs available
-    exec_program(${_nvidia_smi_path} ARGS -L
-      OUTPUT_VARIABLE _nvidia_smi_out
-      RETURN_VALUE _nvidia_smi_ret)
-
-    # process the stdout of nvidia-smi
-    if(_nvidia_smi_ret EQUAL 0)
-      # convert string with newlines to list of strings
-      string(REGEX REPLACE "\n" ";" _nvidia_smi_out "${_nvidia_smi_out}")
-
-      foreach(_line ${_nvidia_smi_out})
-        if(_line MATCHES "^GPU [0-9]+:")
-          math(EXPR DETECT_GPU_COUNT_NVIDIA_SMI "${DETECT_GPU_COUNT_NVIDIA_SMI}+1")
-
-          # the UUID is not very useful for the user, remove it
-          string(REGEX REPLACE " \\(UUID:.*\\)" "" _gpu_info "${_line}")
-
-          if(NOT _gpu_info STREQUAL "")
-            list(APPEND DETECT_GPU_INFO "${_gpu_info}")
-          endif()
-        endif()
-      endforeach()
-
-      check_num_gpu_info(${DETECT_GPU_COUNT_NVIDIA_SMI} DETECT_GPU_INFO)
-      set(DETECT_GPU_COUNT ${DETECT_GPU_COUNT_NVIDIA_SMI})
-    endif()
-  endif()
-
-  # ##
-  if(DETECT_GPU_COUNT GREATER 0)
-    set(CMAKE_CUDA_ARCHITECTURES native) # do native
-  else()
-    # no GPUs found, like on Github CI runners
-    set(CMAKE_CUDA_ARCHITECTURES 50) # some safe value
-  endif()
-endif()
-
 project(icicle LANGUAGES CUDA CXX)
-# Check CUDA version and, if possible, enable multi-threaded compilation 
-if(CMAKE_CUDA_COMPILER_VERSION VERSION_GREATER_EQUAL "12.2")
-    message(STATUS "Using multi-threaded CUDA compilation.")
-    set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} --split-compile 0")
-else()
-    message(STATUS "Can't use multi-threaded CUDA compilation.")
+
+include(cmake/Common.cmake)
+include(cmake/FieldsCommon.cmake)
+include(cmake/CurvesCommon.cmake)
+
+set_env()
+set_gpu_env()
+
+option(DEVMODE "Enable development mode" OFF)
+option(EXT_FIELD "Build extension field" OFF)
+option(G2 "Build G2" OFF)
+option(ECNTT "Build ECNTT" OFF)
+option(BUILD_HASH "Build hash functions" OFF)
+option(BUILD_TESTS "Build unit tests" OFF)
+option(BUILD_BENCHMARKS "Build benchmarks" OFF)
+# add options here
+
+if((DEFINED CURVE) AND (DEFINED FIELD))
+  message( FATAL_ERROR "CURVE and FIELD cannot be defined at the same time" )
+endif ()
+
+if (DEVMODE)
+  set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -O0 --ptxas-options=-O0 --ptxas-options=-allow-expensive-optimizations=false -DDEVMODE=ON")
+endif ()
+
+if(DEFINED FIELD)
+  check_field()
+  add_subdirectory(src/fields)
+endif ()
+
+if(DEFINED CURVE)
+  check_curve()
+  set(FIELD ${CURVE})
+  add_subdirectory(src/fields)
+  add_subdirectory(src/curves)
+endif ()
+
+if (G2)
+  set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -DG2")
+endif ()
+
+if (EXT_FIELD)
+  set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -DEXT_FIELD")
+endif ()
+
+if(BUILD_HASH)
+  add_subdirectory(src/hash)
+endif ()
+
+if (BUILD_TESTS)
+  add_subdirectory(tests)
 endif()
-set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} --expt-relaxed-constexpr")
-set(CMAKE_CUDA_FLAGS_RELEASE "")
-set(CMAKE_CUDA_FLAGS_DEBUG "${CMAKE_CUDA_FLAGS_DEBUG} -g -G -O0")
-include_directories("${CMAKE_SOURCE_DIR}")
 
-
-# when adding a new curve/field, append its name to the end of this list
-set(SUPPORTED_CURVES bn254;bls12_381;bls12_377;bw6_761;grumpkin)
-set(SUPPORTED_CURVES_WITH_POSEIDON bn254;bls12_381;bls12_377;bw6_761;grumpkin)
-SET(SUPPORTED_CURVES_WITHOUT_NTT grumpkin)
-
-set(IS_CURVE_SUPPORTED FALSE)
-set(I 0)
-foreach (SUPPORTED_CURVE ${SUPPORTED_CURVES})
-  math(EXPR I "${I} + 1")
-  if (CURVE STREQUAL SUPPORTED_CURVE)
-    set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -DCURVE_ID=${I}")
-    set(IS_CURVE_SUPPORTED TRUE)
-  endif ()
-endforeach()
-
-if (NOT IS_CURVE_SUPPORTED)
-  message( FATAL_ERROR "The value of CURVE variable: ${CURVE} is not one of the supported curves: ${SUPPORTED_CURVES}" )
-endif ()
-
-if (G2_DEFINED STREQUAL "ON")
-  set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -DG2_DEFINED=ON")
-endif ()
-
-if (ECNTT_DEFINED STREQUAL "ON")
-  set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -DECNTT_DEFINED=ON")
-endif ()
-
-option(BUILD_TESTS "Build tests" OFF)
-
-if (NOT BUILD_TESTS)
-
-  message(STATUS "Building without tests.")
-
-  if (CURVE IN_LIST SUPPORTED_CURVES_WITH_POSEIDON)
-    list(APPEND ICICLE_SOURCES appUtils/poseidon/poseidon.cu)
-    list(APPEND ICICLE_SOURCES appUtils/tree/merkle.cu)
-  endif()
-
-  if (NOT CURVE IN_LIST SUPPORTED_CURVES_WITHOUT_NTT)
-      list(APPEND ICICLE_SOURCES appUtils/ntt/ntt.cu)
-      list(APPEND ICICLE_SOURCES appUtils/ntt/kernel_ntt.cu)
-      if(ECNTT_DEFINED STREQUAL "ON")
-        set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -DECNTT_DEFINED=ON")
-      endif()
-  endif()
-
-  add_library(
-    icicle
-    utils/vec_ops.cu
-    utils/mont.cu
-    primitives/field.cu
-    primitives/projective.cu
-    appUtils/msm/msm.cu
-    ${ICICLE_SOURCES}
-  )
-  set_target_properties(icicle PROPERTIES OUTPUT_NAME "ingo_${CURVE}")
-  target_compile_definitions(icicle PRIVATE CURVE=${CURVE})  
-
-else()
-
-  message(STATUS "Building tests.")
-
-  include(FetchContent)
-  FetchContent_Declare(
-    googletest
-    URL https://github.com/google/googletest/archive/refs/tags/v1.13.0.zip
-  )
-  # For Windows: Prevent overriding the parent project's compiler/linker settings
-
-  set(gtest_force_shared_crt ON CACHE BOOL "" FORCE)
-  FetchContent_MakeAvailable(googletest)
-
-  enable_testing()
-
-  add_executable(
-    runner
-    tests/runner.cu
-  )
-
-  target_link_libraries(
-    runner
-    GTest::gtest_main
-  )
-
-  include(GoogleTest)
-  set_target_properties(runner PROPERTIES CUDA_SEPARABLE_COMPILATION ON)
-
-  gtest_discover_tests(runner)
-
-endif ()
+if (BUILD_BENCHMARKS)
+  add_subdirectory(benchmarks)
+endif()

icicle/appUtils/ntt/Makefile

@@ -1,6 +0,0 @@
-build_verification:
-	mkdir -p work
-	nvcc -o work/test_verification -I. -I.. -I../.. -I../ntt tests/verification.cu -std=c++17
-
-test_verification: build_verification
-	work/test_verification

icicle/benchmarks/CMakeLists.txt

@@ -0,0 +1,5 @@
+
+add_executable(benches benches.cu)
+target_link_libraries(benches benchmark::benchmark)
+target_include_directories(benches PUBLIC ${CMAKE_SOURCE_DIR}/include/)
+find_package(benchmark REQUIRED)

icicle/benchmarks/README.md

@@ -0,0 +1,25 @@
+# How to use benchmarks
+
+ICICLE uses [google benchmarks](https://github.com/google/benchmark) to measure the performance of primitives.
+
+To run benchmarks, make sure you have everything installed to run ICICLE (see top-level README for that). Next, you need to install google benchmarks library as described in their [documentation](https://github.com/google/benchmark?tab=readme-ov-file#installation). When running benchmarks, export the path to this installation:
+
+```
+export CMAKE_PREFIX_PATH=$CMAKE_PREFIX_PATH:<path-to-google-benchmarks-build-folder>
+```
+
+Then to benchmark field arithmetic, say, on `baby_bear` field, run:
+
+```
+cmake -UCURVE -UFIELD -UG2 -UEXT_FIELD -DFIELD=babybear -DEXT_FIELD=ON -S . -B build;
+cmake --build build;
+build/benches --benchmark_counters_tabular=true
+```
+
+`-U` parameters are needed to clear variables from previous runs and `EXT_FIELD` can be disabled if benhcmarking the extension field is not needed. To benchmark a curve, say, `bn254`, change the first `cmake` call to:
+
+```
+cmake -UCURVE -UFIELD -UG2 -UEXT_FIELD -DCURVE=bn254 -S . -B build;
+```
+
+Benchmarks measure throughput of very cheap operations like field multiplication or EC addition by repeating them very many times in parallel, so throughput is the main metric to look at.

icicle/benchmarks/benches.cu

@@ -0,0 +1,6 @@
+#include "field_benchmarks.cu"
+#ifdef CURVE_ID
+#include "curve_benchmarks.cu"
+#endif
+
+BENCHMARK_MAIN();

icicle/benchmarks/curve_benchmarks.cu

@@ -0,0 +1,79 @@
+#include <benchmark/benchmark.h>
+#include "utils/test_functions.cuh"
+#include "curves/curve_config.cuh"
+
+using namespace curve_config;
+using namespace benchmark;
+
+static void BM_MixedECAdd(State& state)
+{
+  constexpr int N = 128;
+  int n = state.range(0) / N;
+  projective_t* points1;
+  affine_t* points2;
+  assert(!cudaMalloc(&points1, n * sizeof(projective_t)));
+  assert(!cudaMalloc(&points2, n * sizeof(affine_t)));
+
+  projective_t* h_points1 = (projective_t*)malloc(n * sizeof(projective_t));
+  affine_t* h_points2 = (affine_t*)malloc(n * sizeof(affine_t));
+  projective_t::RandHostMany(h_points1, n);
+  projective_t::RandHostManyAffine(h_points2, n);
+  cudaMemcpy(points1, h_points1, sizeof(projective_t) * n, cudaMemcpyHostToDevice);
+  cudaMemcpy(points2, h_points2, sizeof(affine_t) * n, cudaMemcpyHostToDevice);
+
+  for (auto _ : state) {
+    cudaEvent_t start, stop;
+    cudaEventCreate(&start);
+    cudaEventCreate(&stop);
+    cudaEventRecord(start);
+    assert((vec_add<projective_t, affine_t, N>(points1, points2, points1, n)) == cudaSuccess);
+    assert(cudaStreamSynchronize(0) == cudaSuccess);
+    cudaEventRecord(stop);
+
+    float milliseconds = 0;
+    cudaEventElapsedTime(&milliseconds, start, stop);
+
+    state.SetIterationTime((double)(milliseconds / 1000));
+  }
+  state.counters["Throughput"] = Counter(state.range(0), Counter::kIsRate | Counter::kIsIterationInvariant);
+  cudaFree(points1);
+  cudaFree(points2);
+}
+
+static void BM_FullECAdd(benchmark::State& state)
+{
+  constexpr int N = 128;
+  int n = state.range(0) / N;
+  projective_t* points1;
+  projective_t* points2;
+  assert(!cudaMalloc(&points1, n * sizeof(projective_t)));
+  assert(!cudaMalloc(&points2, n * sizeof(projective_t)));
+
+  projective_t* h_points1 = (projective_t*)malloc(n * sizeof(projective_t));
+  projective_t* h_points2 = (projective_t*)malloc(n * sizeof(projective_t));
+  projective_t::RandHostMany(h_points1, n);
+  projective_t::RandHostMany(h_points2, n);
+  cudaMemcpy(points1, h_points1, sizeof(projective_t) * n, cudaMemcpyHostToDevice);
+  cudaMemcpy(points2, h_points2, sizeof(projective_t) * n, cudaMemcpyHostToDevice);
+
+  for (auto _ : state) {
+    cudaEvent_t start, stop;
+    cudaEventCreate(&start);
+    cudaEventCreate(&stop);
+    cudaEventRecord(start);
+    assert((vec_add<projective_t, projective_t, N>(points1, points2, points1, n)) == cudaSuccess);
+    assert(cudaStreamSynchronize(0) == cudaSuccess);
+    cudaEventRecord(stop);
+
+    float milliseconds = 0;
+    cudaEventElapsedTime(&milliseconds, start, stop);
+
+    state.SetIterationTime((double)(milliseconds / 1000));
+  }
+  state.counters["Throughput"] = Counter(state.range(0), Counter::kIsRate | Counter::kIsIterationInvariant);
+  cudaFree(points1);
+  cudaFree(points2);
+}
+
+BENCHMARK(BM_FullECAdd)->Range(1 << 27, 1 << 27)->Unit(benchmark::kMillisecond);
+BENCHMARK(BM_MixedECAdd)->Range(1 << 27, 1 << 27)->Unit(benchmark::kMillisecond);

icicle/benchmarks/field_benchmarks.cu

@@ -0,0 +1,108 @@
+#include <benchmark/benchmark.h>
+#include "utils/test_functions.cuh"
+#include "fields/field_config.cuh"
+
+using namespace field_config;
+using namespace benchmark;
+
+template <class T>
+static void BM_FieldAdd(State& state)
+{
+  constexpr int N = 256;
+  int n = state.range(0) / N;
+  T* scalars1;
+  T* scalars2;
+  assert(!cudaMalloc(&scalars1, n * sizeof(T)));
+  assert(!cudaMalloc(&scalars2, n * sizeof(T)));
+
+  assert(device_populate_random<T>(scalars1, n) == cudaSuccess);
+  assert(device_populate_random<T>(scalars2, n) == cudaSuccess);
+
+  for (auto _ : state) {
+    cudaEvent_t start, stop;
+    cudaEventCreate(&start);
+    cudaEventCreate(&stop);
+    cudaEventRecord(start);
+    assert((vec_add<T, T, N>(scalars1, scalars2, scalars1, n)) == cudaSuccess);
+    assert(cudaStreamSynchronize(0) == cudaSuccess);
+    cudaEventRecord(stop);
+
+    float milliseconds = 0;
+    cudaEventElapsedTime(&milliseconds, start, stop);
+
+    state.SetIterationTime((double)(milliseconds / 1000));
+  }
+  state.counters["Throughput"] = Counter(state.range(0), Counter::kIsRate | Counter::kIsIterationInvariant);
+  cudaFree(scalars1);
+  cudaFree(scalars2);
+}
+
+template <class T>
+static void BM_FieldMul(State& state)
+{
+  constexpr int N = 128;
+  int n = state.range(0) / N;
+  T* scalars1;
+  T* scalars2;
+  assert(!cudaMalloc(&scalars1, n * sizeof(T)));
+  assert(!cudaMalloc(&scalars2, n * sizeof(T)));
+
+  assert(device_populate_random<T>(scalars1, n) == cudaSuccess);
+  assert(device_populate_random<T>(scalars2, n) == cudaSuccess);
+
+  for (auto _ : state) {
+    cudaEvent_t start, stop;
+    cudaEventCreate(&start);
+    cudaEventCreate(&stop);
+    cudaEventRecord(start);
+    assert((vec_mul<T, T, N>(scalars1, scalars2, scalars1, n)) == cudaSuccess);
+    assert(cudaStreamSynchronize(0) == cudaSuccess);
+    cudaEventRecord(stop);
+
+    float milliseconds = 0;
+    cudaEventElapsedTime(&milliseconds, start, stop);
+
+    state.SetIterationTime((double)(milliseconds / 1000));
+  }
+  state.counters["Throughput"] = Counter(state.range(0), Counter::kIsRate | Counter::kIsIterationInvariant);
+  cudaFree(scalars1);
+  cudaFree(scalars2);
+}
+
+template <class T>
+static void BM_FieldSqr(State& state)
+{
+  constexpr int N = 128;
+  int n = state.range(0) / N;
+  T* scalars;
+  assert(!cudaMalloc(&scalars, n * sizeof(T)));
+
+  assert(device_populate_random<T>(scalars, n) == cudaSuccess);
+
+  for (auto _ : state) {
+    cudaEvent_t start, stop;
+    cudaEventCreate(&start);
+    cudaEventCreate(&stop);
+    cudaEventRecord(start);
+    assert((field_vec_sqr<T, N>(scalars, scalars, n)) == cudaSuccess);
+    assert(cudaStreamSynchronize(0) == cudaSuccess);
+    cudaEventRecord(stop);
+
+    float milliseconds = 0;
+    cudaEventElapsedTime(&milliseconds, start, stop);
+
+    state.SetIterationTime((double)(milliseconds / 1000));
+  }
+  state.counters["Throughput"] = Counter(state.range(0), Counter::kIsRate | Counter::kIsIterationInvariant);
+  cudaFree(scalars);
+}
+
+BENCHMARK(BM_FieldAdd<scalar_t>)->Range(1 << 28, 1 << 28)->Unit(kMicrosecond);
+BENCHMARK(BM_FieldMul<scalar_t>)->Range(1 << 27, 1 << 27)->Unit(kMicrosecond);
+BENCHMARK(BM_FieldSqr<scalar_t>)->Range(1 << 27, 1 << 27)->Unit(kMicrosecond);
+
+#ifdef EXT_FIELD
+BENCHMARK(BM_FieldAdd<extension_t>)->Range(1 << 28, 1 << 28)->Unit(kMicrosecond);
+BENCHMARK(BM_FieldMul<extension_t>)->Range(1 << 27, 1 << 27)->Unit(kMicrosecond);
+BENCHMARK(BM_FieldSqr<extension_t>)->Range(1 << 27, 1 << 27)->Unit(kMicrosecond);
+#endif

icicle/cmake/Common.cmake

@@ -0,0 +1,72 @@
+function(set_env)
+    set(CMAKE_CXX_STANDARD 17 PARENT_SCOPE)
+    set(CMAKE_CUDA_STANDARD 17 PARENT_SCOPE)
+    set(CMAKE_CUDA_STANDARD_REQUIRED TRUE PARENT_SCOPE)
+    set(CMAKE_CXX_STANDARD_REQUIRED TRUE PARENT_SCOPE)
+
+    if("$ENV{ICICLE_PIC}" STREQUAL "OFF" OR ICICLE_PIC STREQUAL "OFF")
+        message(WARNING "Note that PIC (position-independent code) is disabled.")
+    else()
+        set(CMAKE_POSITION_INDEPENDENT_CODE ON)
+    endif()
+endfunction()
+
+function(set_gpu_env)
+    # add the target cuda architectures
+    # each additional architecture increases the compilation time and output file size
+    if(${CMAKE_VERSION} VERSION_LESS "3.24.0")
+    set(CMAKE_CUDA_ARCHITECTURES ${CUDA_ARCH} PARENT_SCOPE)
+    else()
+    find_program(_nvidia_smi "nvidia-smi")
+
+    if(_nvidia_smi)
+        set(DETECT_GPU_COUNT_NVIDIA_SMI 0)
+
+        # execute nvidia-smi -L to get a short list of GPUs available
+        exec_program(${_nvidia_smi_path} ARGS -L
+        OUTPUT_VARIABLE _nvidia_smi_out
+        RETURN_VALUE _nvidia_smi_ret)
+
+        # process the stdout of nvidia-smi
+        if(_nvidia_smi_ret EQUAL 0)
+        # convert string with newlines to list of strings
+        string(REGEX REPLACE "\n" ";" _nvidia_smi_out "${_nvidia_smi_out}")
+
+        foreach(_line ${_nvidia_smi_out})
+            if(_line MATCHES "^GPU [0-9]+:")
+            math(EXPR DETECT_GPU_COUNT_NVIDIA_SMI "${DETECT_GPU_COUNT_NVIDIA_SMI}+1")
+
+            # the UUID is not very useful for the user, remove it
+            string(REGEX REPLACE " \\(UUID:.*\\)" "" _gpu_info "${_line}")
+
+            if(NOT _gpu_info STREQUAL "")
+                list(APPEND DETECT_GPU_INFO "${_gpu_info}")
+            endif()
+            endif()
+        endforeach()
+
+        check_num_gpu_info(${DETECT_GPU_COUNT_NVIDIA_SMI} DETECT_GPU_INFO)
+        set(DETECT_GPU_COUNT ${DETECT_GPU_COUNT_NVIDIA_SMI})
+        endif()
+    endif()
+
+    # ##
+    if(DETECT_GPU_COUNT GREATER 0)
+        set(CMAKE_CUDA_ARCHITECTURES native PARENT_SCOPE) # do native
+    else()
+        # no GPUs found, like on Github CI runners
+        set(CMAKE_CUDA_ARCHITECTURES 50 PARENT_SCOPE) # some safe value
+    endif()
+    endif()
+
+    # Check CUDA version and, if possible, enable multi-threaded compilation 
+    if(CMAKE_CUDA_COMPILER_VERSION VERSION_GREATER_EQUAL "12.2")
+        message(STATUS "Using multi-threaded CUDA compilation.")
+        set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} --split-compile 0" PARENT_SCOPE)
+    else()
+        message(STATUS "Can't use multi-threaded CUDA compilation.")
+    endif()
+    set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} --expt-relaxed-constexpr" PARENT_SCOPE)
+    set(CMAKE_CUDA_FLAGS_RELEASE "" PARENT_SCOPE)
+    set(CMAKE_CUDA_FLAGS_DEBUG "${CMAKE_CUDA_FLAGS_DEBUG} -g -lineinfo" PARENT_SCOPE)
+endfunction()

icicle/cmake/CurvesCommon.cmake

@@ -0,0 +1,17 @@
+function(check_curve)
+  set(SUPPORTED_CURVES bn254;bls12_381;bls12_377;bw6_761;grumpkin)
+
+  set(IS_CURVE_SUPPORTED FALSE)
+  set(I 0)
+  foreach (SUPPORTED_CURVE ${SUPPORTED_CURVES})
+    math(EXPR I "${I} + 1")
+    if (CURVE STREQUAL SUPPORTED_CURVE)
+      set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -DCURVE_ID=${I} -DFIELD_ID=${I}" PARENT_SCOPE)
+      set(IS_CURVE_SUPPORTED TRUE)
+    endif ()
+  endforeach()
+
+  if (NOT IS_CURVE_SUPPORTED)
+    message( FATAL_ERROR "The value of CURVE variable: ${CURVE} is not one of the supported curves: ${SUPPORTED_CURVES}" )
+  endif ()
+endfunction()

icicle/cmake/FieldsCommon.cmake

@@ -0,0 +1,17 @@
+function(check_field)
+  set(SUPPORTED_FIELDS babybear)
+
+  set(IS_FIELD_SUPPORTED FALSE)
+  set(I 1000)
+  foreach (SUPPORTED_FIELD ${SUPPORTED_FIELDS})
+    math(EXPR I "${I} + 1")
+    if (FIELD STREQUAL SUPPORTED_FIELD)
+      set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -DFIELD_ID=${I}" PARENT_SCOPE)
+      set(IS_FIELD_SUPPORTED TRUE)
+    endif ()
+  endforeach()
+
+  if (NOT IS_FIELD_SUPPORTED)
+    message( FATAL_ERROR "The value of FIELD variable: ${FIELD} is not one of the supported fields: ${SUPPORTED_FIELDS}" )
+  endif ()
+endfunction()

icicle/include/curves/affine.cuh

@@ -1,6 +1,8 @@
 #pragma once
 
-#include "field.cuh"
+#include "gpu-utils/sharedmem.cuh"
+#include "gpu-utils/modifiers.cuh"
+#include <iostream>
 
 template <class FF>
 class Affine
@@ -33,4 +35,13 @@ public:
     os << "x: " << point.x << "; y: " << point.y;
     return os;
   }
-};
+};
+
+template <class FF>
+struct SharedMemory<Affine<FF>> {
+  __device__ Affine<FF>* getPointer()
+  {
+    extern __shared__ Affine<FF> s_affine_[];
+    return s_affine_;
+  }
+};

icicle/include/curves/curve_config.cuh

@@ -1,36 +1,38 @@
 #pragma once
-#ifndef INDEX_H
-#define INDEX_H
+#ifndef CURVE_CONFIG_H
+#define CURVE_CONFIG_H
 
-#define BN254     1
-#define BLS12_381 2
-#define BLS12_377 3
-#define BW6_761   4
-#define GRUMPKIN  5
-
-#include "primitives/field.cuh"
-#include "primitives/projective.cuh"
-#if defined(G2_DEFINED)
-#include "primitives/extension_field.cuh"
-#endif
+#include "fields/id.h"
+#include "curves/projective.cuh"
 
 #if CURVE_ID == BN254
-#include "bn254_params.cuh"
+#include "curves/params/bn254.cuh"
 using namespace bn254;
+
 #elif CURVE_ID == BLS12_381
-#include "bls12_381_params.cuh"
+#include "curves/params/bls12_381.cuh"
 using namespace bls12_381;
+
 #elif CURVE_ID == BLS12_377
-#include "bls12_377_params.cuh"
+#include "curves/params/bls12_377.cuh"
 using namespace bls12_377;
+
 #elif CURVE_ID == BW6_761
-#include "bw6_761_params.cuh"
+#include "curves/params/bw6_761.cuh"
 using namespace bw6_761;
+
 #elif CURVE_ID == GRUMPKIN
-#include "grumpkin_params.cuh"
+#include "curves/params/grumpkin.cuh"
 using namespace grumpkin;
 #endif
 
+#include "fields/field_config.cuh"
+using field_config::scalar_t;
+
+#ifdef G2
+#include "fields/quadratic_extension.cuh"
+#endif
+
 /**
  * @namespace curve_config
  * Namespace with type definitions for short Weierstrass pairing-friendly [elliptic
@@ -38,14 +40,11 @@ using namespace grumpkin;
  * with the `-DCURVE` env variable passed during build.
  */
 namespace curve_config {
-  /**
-   * Scalar field of the curve. Is always a prime field.
-   */
-  typedef Field<fp_config> scalar_t;
   /**
    * Base field of G1 curve. Is always a prime field.
    */
   typedef Field<fq_config> point_field_t;
+
   static constexpr point_field_t generator_x = point_field_t{g1_gen_x};
   static constexpr point_field_t generator_y = point_field_t{g1_gen_y};
   static constexpr point_field_t b = point_field_t{weierstrass_b};
@@ -59,7 +58,7 @@ namespace curve_config {
    */
   typedef Affine<point_field_t> affine_t;
 
-#if defined(G2_DEFINED)
+#ifdef G2
 #if CURVE_ID == BW6_761
   typedef point_field_t g2_point_field_t;
   static constexpr g2_point_field_t g2_generator_x = g2_point_field_t{g2_gen_x};
@@ -74,6 +73,7 @@ namespace curve_config {
   static constexpr g2_point_field_t g2_b =
     g2_point_field_t{point_field_t{weierstrass_b_g2_re}, point_field_t{weierstrass_b_g2_im}};
 #endif
+
   /**
    * [Projective representation](https://hyperelliptic.org/EFD/g1p/auto-shortw-projective.html) of G2 curve.
    */

icicle/include/curves/params/bls12_377.cuh

@@ -0,0 +1,40 @@
+#pragma once
+#ifndef BLS12_377_PARAMS_H
+#define BLS12_377_PARAMS_H
+
+#include "fields/storage.cuh"
+#include "fields/snark_fields/bls12_377_base.cuh"
+
+namespace bls12_377 {
+  // G1 and G2 generators
+  static constexpr storage<fq_config::limbs_count> g1_gen_x = {0xb21be9ef, 0xeab9b16e, 0xffcd394e, 0xd5481512,
+                                                               0xbd37cb5c, 0x188282c8, 0xaa9d41bb, 0x85951e2c,
+                                                               0xbf87ff54, 0xc8fc6225, 0xfe740a67, 0x008848de};
+  static constexpr storage<fq_config::limbs_count> g1_gen_y = {0x559c8ea6, 0xfd82de55, 0x34a9591a, 0xc2fe3d36,
+                                                               0x4fb82305, 0x6d182ad4, 0xca3e52d9, 0xbd7fb348,
+                                                               0x30afeec4, 0x1f674f5d, 0xc5102eff, 0x01914a69};
+  static constexpr storage<fq_config::limbs_count> g2_gen_x_re = {0x7c005196, 0x74e3e48f, 0xbb535402, 0x71889f52,
+                                                                  0x57db6b9b, 0x7ea501f5, 0x203e5031, 0xc565f071,
+                                                                  0xa3841d01, 0xc89630a2, 0x71c785fe, 0x018480be};
+  static constexpr storage<fq_config::limbs_count> g2_gen_x_im = {0x6ea16afe, 0xb26bfefa, 0xbff76fe6, 0x5cf89984,
+                                                                  0x0799c9de, 0xe7223ece, 0x6651cecb, 0x532777ee,
+                                                                  0xb1b140d5, 0x70dc5a51, 0xe7004031, 0x00ea6040};
+  static constexpr storage<fq_config::limbs_count> g2_gen_y_re = {0x09fd4ddf, 0xf0940944, 0x6d8c7c2e, 0xf2cf8888,
+                                                                  0xf832d204, 0xe458c282, 0x74b49a58, 0xde03ed72,
+                                                                  0xcbb2efb4, 0xd960736b, 0x5d446f7b, 0x00690d66};
+  static constexpr storage<fq_config::limbs_count> g2_gen_y_im = {0x85eb8f93, 0xd9a1cdd1, 0x5e52270b, 0x4279b83f,
+                                                                  0xcee304c2, 0x2463b01a, 0x3d591bf1, 0x61ef11ac,
+                                                                  0x151a70aa, 0x9e549da3, 0xd2835518, 0x00f8169f};
+
+  static constexpr storage<fq_config::limbs_count> weierstrass_b = {0x00000001, 0x00000000, 0x00000000, 0x00000000,
+                                                                    0x00000000, 0x00000000, 0x00000000, 0x00000000,
+                                                                    0x00000000, 0x00000000, 0x00000000, 0x00000000};
+  static constexpr storage<fq_config::limbs_count> weierstrass_b_g2_re = {
+    0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000,
+    0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000};
+  static constexpr storage<fq_config::limbs_count> weierstrass_b_g2_im = {
+    0x9999999a, 0x1c9ed999, 0x1ccccccd, 0x0dd39e5c, 0x3c6bf800, 0x129207b6,
+    0xcd5fd889, 0xdc7b4f91, 0x7460c589, 0x43bd0373, 0xdb0fd6f3, 0x010222f6};
+} // namespace bls12_377
+
+#endif

icicle/include/curves/params/bls12_381.cuh

@@ -0,0 +1,40 @@
+#pragma once
+#ifndef BLS12_381_PARAMS_H
+#define BLS12_381_PARAMS_H
+
+#include "fields/storage.cuh"
+#include "fields/snark_fields/bls12_381_base.cuh"
+
+namespace bls12_381 {
+  // G1 and G2 generators
+  static constexpr storage<fq_config::limbs_count> g1_gen_x = {0xdb22c6bb, 0xfb3af00a, 0xf97a1aef, 0x6c55e83f,
+                                                               0x171bac58, 0xa14e3a3f, 0x9774b905, 0xc3688c4f,
+                                                               0x4fa9ac0f, 0x2695638c, 0x3197d794, 0x17f1d3a7};
+  static constexpr storage<fq_config::limbs_count> g1_gen_y = {0x46c5e7e1, 0x0caa2329, 0xa2888ae4, 0xd03cc744,
+                                                               0x2c04b3ed, 0x00db18cb, 0xd5d00af6, 0xfcf5e095,
+                                                               0x741d8ae4, 0xa09e30ed, 0xe3aaa0f1, 0x08b3f481};
+  static constexpr storage<fq_config::limbs_count> g2_gen_x_re = {0xc121bdb8, 0xd48056c8, 0xa805bbef, 0x0bac0326,
+                                                                  0x7ae3d177, 0xb4510b64, 0xfa403b02, 0xc6e47ad4,
+                                                                  0x2dc51051, 0x26080527, 0xf08f0a91, 0x024aa2b2};
+  static constexpr storage<fq_config::limbs_count> g2_gen_x_im = {0x5d042b7e, 0xe5ac7d05, 0x13945d57, 0x334cf112,
+                                                                  0xdc7f5049, 0xb5da61bb, 0x9920b61a, 0x596bd0d0,
+                                                                  0x88274f65, 0x7dacd3a0, 0x52719f60, 0x13e02b60};
+  static constexpr storage<fq_config::limbs_count> g2_gen_y_re = {0x08b82801, 0xe1935486, 0x3baca289, 0x923ac9cc,
+                                                                  0x5160d12c, 0x6d429a69, 0x8cbdd3a7, 0xadfd9baa,
+                                                                  0xda2e351a, 0x8cc9cdc6, 0x727d6e11, 0x0ce5d527};
+  static constexpr storage<fq_config::limbs_count> g2_gen_y_im = {0xf05f79be, 0xaaa9075f, 0x5cec1da1, 0x3f370d27,
+                                                                  0x572e99ab, 0x267492ab, 0x85a763af, 0xcb3e287e,
+                                                                  0x2bc28b99, 0x32acd2b0, 0x2ea734cc, 0x0606c4a0};
+
+  static constexpr storage<fq_config::limbs_count> weierstrass_b = {0x00000004, 0x00000000, 0x00000000, 0x00000000,
+                                                                    0x00000000, 0x00000000, 0x00000000, 0x00000000,
+                                                                    0x00000000, 0x00000000, 0x00000000, 0x00000000};
+  static constexpr storage<fq_config::limbs_count> weierstrass_b_g2_re = {
+    0x00000004, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000,
+    0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000};
+  static constexpr storage<fq_config::limbs_count> weierstrass_b_g2_im = {
+    0x00000004, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000,
+    0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000};
+} // namespace bls12_381
+
+#endif

icicle/include/curves/params/bn254.cuh

@@ -0,0 +1,31 @@
+#pragma once
+#ifndef BN254_PARAMS_H
+#define BN254_PARAMS_H
+
+#include "fields/storage.cuh"
+#include "fields/snark_fields/bn254_base.cuh"
+
+namespace bn254 {
+  // G1 and G2 generators
+  static constexpr storage<fq_config::limbs_count> g1_gen_x = {0x00000001, 0x00000000, 0x00000000, 0x00000000,
+                                                               0x00000000, 0x00000000, 0x00000000, 0x00000000};
+  static constexpr storage<fq_config::limbs_count> g1_gen_y = {0x00000002, 0x00000000, 0x00000000, 0x00000000,
+                                                               0x00000000, 0x00000000, 0x00000000, 0x00000000};
+  static constexpr storage<fq_config::limbs_count> g2_gen_x_re = {0xd992f6ed, 0x46debd5c, 0xf75edadd, 0x674322d4,
+                                                                  0x5e5c4479, 0x426a0066, 0x121f1e76, 0x1800deef};
+  static constexpr storage<fq_config::limbs_count> g2_gen_x_im = {0xaef312c2, 0x97e485b7, 0x35a9e712, 0xf1aa4933,
+                                                                  0x31fb5d25, 0x7260bfb7, 0x920d483a, 0x198e9393};
+  static constexpr storage<fq_config::limbs_count> g2_gen_y_re = {0x66fa7daa, 0x4ce6cc01, 0x0c43d37b, 0xe3d1e769,
+                                                                  0x8dcb408f, 0x4aab7180, 0xdb8c6deb, 0x12c85ea5};
+  static constexpr storage<fq_config::limbs_count> g2_gen_y_im = {0xd122975b, 0x55acdadc, 0x70b38ef3, 0xbc4b3133,
+                                                                  0x690c3395, 0xec9e99ad, 0x585ff075, 0x090689d0};
+
+  static constexpr storage<fq_config::limbs_count> weierstrass_b = {0x00000003, 0x00000000, 0x00000000, 0x00000000,
+                                                                    0x00000000, 0x00000000, 0x00000000, 0x00000000};
+  static constexpr storage<fq_config::limbs_count> weierstrass_b_g2_re = {
+    0x24a138e5, 0x3267e6dc, 0x59dbefa3, 0xb5b4c5e5, 0x1be06ac3, 0x81be1899, 0xceb8aaae, 0x2b149d40};
+  static constexpr storage<fq_config::limbs_count> weierstrass_b_g2_im = {
+    0x85c315d2, 0xe4a2bd06, 0xe52d1852, 0xa74fa084, 0xeed8fdf4, 0xcd2cafad, 0x3af0fed4, 0x009713b0};
+} // namespace bn254
+
+#endif

icicle/include/curves/params/bw6_761.cuh

@@ -0,0 +1,37 @@
+#pragma once
+#ifndef BW6_761_PARAMS_H
+#define BW6_761_PARAMS_H
+
+#include "fields/storage.cuh"
+#include "fields/snark_fields/bw6_761_base.cuh"
+
+namespace bw6_761 {
+  // G1 and G2 generators
+  static constexpr storage<fq_config::limbs_count> g1_gen_x = {
+    0x66e5b43d, 0x4088f3af, 0xa6af603f, 0x055928ac, 0x56133e82, 0x6750dd03, 0x280ca27f, 0x03758f9a,
+    0xc9ea0971, 0x5bd71fa0, 0x47729b90, 0xa17a54ce, 0x94c2e746, 0x11dbfcd2, 0xc15520ac, 0x79017ffa,
+    0x85f56fc7, 0xee05c54b, 0x551b27f0, 0xe6a0cfb7, 0xa477beae, 0xb277ce98, 0x0ea190c8, 0x01075b02};
+  static constexpr storage<fq_config::limbs_count> g1_gen_y = {
+    0xb4e95363, 0xbafc8f2d, 0x0b20d2a1, 0xad1cb2be, 0xcad0fb93, 0xb2b08119, 0xb3053253, 0x9f9df141,
+    0x6fc2cdd4, 0xbe3fb90b, 0x717a4c55, 0xcc685d31, 0x71b5b806, 0xc5b8fa17, 0xaf7e0dba, 0x265909f1,
+    0xa2e573a3, 0x1a7348d2, 0x884c9ec6, 0x0f952589, 0x45cc2a42, 0xe6fd637b, 0x0a6fc574, 0x0058b84e};
+  static constexpr storage<fq_config::limbs_count> g2_gen_x = {
+    0xcd025f1c, 0xa830c194, 0xe1bf995b, 0x6410cf4f, 0xc2ad54b0, 0x00e96efb, 0x3cd208d7, 0xce6948cb,
+    0x00e1b6ba, 0x963317a3, 0xac70e7c7, 0xc5bbcae9, 0xf09feb58, 0x734ec3f1, 0xab3da268, 0x26b41c5d,
+    0x13890f6d, 0x4c062010, 0xc5a7115f, 0xd61053aa, 0x69d660f9, 0xc852a82e, 0x41d9b816, 0x01101332};
+  static constexpr storage<fq_config::limbs_count> g2_gen_y = {
+    0x28c73b61, 0xeb70a167, 0xf9eac689, 0x91ec0594, 0x3c5a02a5, 0x58aa2d3a, 0x504affc7, 0x3ea96fcd,
+    0xffa82300, 0x8906c170, 0xd2c712b8, 0x64f293db, 0x33293fef, 0x94c97eb7, 0x0b95a59c, 0x0a1d86c8,
+    0x53ffe316, 0x81a78e27, 0xcec2181c, 0x26b7cf9a, 0xe4b6d2dc, 0x8179eb10, 0x7761369f, 0x0017c335};
+
+  static constexpr storage<fq_config::limbs_count> weierstrass_b = {
+    0x0000008a, 0xf49d0000, 0x70000082, 0xe6913e68, 0xeaf0a437, 0x160cf8ae, 0x5667a8f8, 0x98a116c2,
+    0x73ebff2e, 0x71dcd3dc, 0x12f9fd90, 0x8689c8ed, 0x25b42304, 0x03cebaff, 0xe584e919, 0x707ba638,
+    0x8087be41, 0x528275ef, 0x81d14688, 0xb926186a, 0x04faff3e, 0xd187c940, 0xfb83ce0a, 0x0122e824};
+  static constexpr storage<fq_config::limbs_count> g2_weierstrass_b = {
+    0x00000004, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000,
+    0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000,
+    0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000};
+} // namespace bw6_761
+
+#endif

icicle/include/curves/params/grumpkin.cuh

@@ -2,13 +2,11 @@
 #ifndef GRUMPKIN_PARAMS_H
 #define GRUMPKIN_PARAMS_H
 
-#include "utils/storage.cuh"
-#include "bn254_params.cuh"
+#include "fields/storage.cuh"
+#include "fields/snark_fields/bn254_scalar.cuh"
 
 namespace grumpkin {
-  typedef bn254::fq_config fp_config;
   typedef bn254::fp_config fq_config;
-
   // G1 generator
   static constexpr storage<fq_config::limbs_count> g1_gen_x = {0x00000001, 0x00000000, 0x00000000, 0x00000000,
                                                                0x00000000, 0x00000000, 0x00000000, 0x00000000};

icicle/include/curves/projective.cuh

@@ -1,6 +1,7 @@
 #pragma once
 
 #include "affine.cuh"
+#include "gpu-utils/sharedmem.cuh"
 
 template <typename FF, class SCALAR_FF, const FF& B_VALUE, const FF& GENERATOR_X, const FF& GENERATOR_Y>
 class Projective
@@ -8,6 +9,9 @@ class Projective
   friend Affine<FF>;
 
 public:
+  typedef Affine<FF> Aff;
+  typedef SCALAR_FF Scalar;
+
   static constexpr unsigned SCALAR_FF_NBITS = SCALAR_FF::NBITS;
   static constexpr unsigned FF_NBITS = FF::NBITS;
 
@@ -23,7 +27,10 @@ public:
     return {point.x * denom, point.y * denom};
   }
 
-  static HOST_DEVICE_INLINE Projective from_affine(const Affine<FF>& point) { return {point.x, point.y, FF::one()}; }
+  static HOST_DEVICE_INLINE Projective from_affine(const Affine<FF>& point)
+  {
+    return point == Affine<FF>::zero() ? zero() : Projective{point.x, point.y, FF::one()};
+  }
 
   static HOST_DEVICE_INLINE Projective ToMontgomery(const Projective& point)
   {
@@ -165,7 +172,7 @@ public:
   {
     Projective res = zero();
 #ifdef __CUDA_ARCH__
-#pragma unroll
+    UNROLL
 #endif
     for (int i = 0; i < SCALAR_FF::NBITS; i++) {
       if (i > 0) { res = res + res; }
@@ -221,3 +228,12 @@ public:
       out[i] = (i % size < 100) ? to_affine(rand_host()) : out[i - 100];
   }
 };
+
+template <typename FF, class SCALAR_FF, const FF& B_VALUE, const FF& GENERATOR_X, const FF& GENERATOR_Y>
+struct SharedMemory<Projective<FF, SCALAR_FF, B_VALUE, GENERATOR_X, GENERATOR_Y>> {
+  __device__ Projective<FF, SCALAR_FF, B_VALUE, GENERATOR_X, GENERATOR_Y>* getPointer()
+  {
+    extern __shared__ Projective<FF, SCALAR_FF, B_VALUE, GENERATOR_X, GENERATOR_Y> s_projective_[];
+    return s_projective_;
+  }
+};

icicle/include/fields/field.cuh

@@ -18,20 +18,19 @@
 
 #pragma once
 
-#include "utils/error_handler.cuh"
-#include "utils/host_math.cuh"
-#include "utils/ptx.cuh"
-#include "utils/storage.cuh"
+#include "gpu-utils/error_handler.cuh"
+#include "gpu-utils/modifiers.cuh"
+#include "gpu-utils/sharedmem.cuh"
+#include "host_math.cuh"
+#include "ptx.cuh"
+#include "storage.cuh"
+
 #include <iomanip>
 #include <iostream>
 #include <random>
 #include <sstream>
 #include <string>
 
-#define HOST_INLINE        __host__ __forceinline__
-#define DEVICE_INLINE      __device__ __forceinline__
-#define HOST_DEVICE_INLINE __host__ __device__ __forceinline__
-
 template <class CONFIG>
 class Field
 {
@@ -130,7 +129,7 @@ public:
     {
       Field out{};
 #ifdef __CUDA_ARCH__
-#pragma unroll
+      UNROLL
 #endif
       for (unsigned i = 0; i < TLC; i++)
         out.limbs_storage.limbs[i] = xs.limbs_storage.limbs[i];
@@ -141,7 +140,7 @@ public:
     {
       Field out{};
 #ifdef __CUDA_ARCH__
-#pragma unroll
+      UNROLL
 #endif
       for (unsigned i = 0; i < TLC; i++)
         out.limbs_storage.limbs[i] = xs.limbs_storage.limbs[i + TLC];
@@ -152,7 +151,7 @@ public:
     {
       Field out{};
 #ifdef __CUDA_ARCH__
-#pragma unroll
+      UNROLL
 #endif
       for (unsigned i = 0; i < TLC; i++) {
 #ifdef __CUDA_ARCH__
@@ -244,14 +243,14 @@ public:
   }
 
   template <bool SUBTRACT, bool CARRY_OUT>
-  static constexpr __device__ __forceinline__ uint32_t
+  static constexpr DEVICE_INLINE uint32_t
   add_sub_u32_device(const uint32_t* x, const uint32_t* y, uint32_t* r, size_t n = (TLC >> 1))
   {
     r[0] = SUBTRACT ? ptx::sub_cc(x[0], y[0]) : ptx::add_cc(x[0], y[0]);
-    for (unsigned i = 1; i < (CARRY_OUT ? n : n - 1); i++)
+    for (unsigned i = 1; i < n; i++)
       r[i] = SUBTRACT ? ptx::subc_cc(x[i], y[i]) : ptx::addc_cc(x[i], y[i]);
     if (!CARRY_OUT) {
-      r[n - 1] = SUBTRACT ? ptx::subc(x[n - 1], y[n - 1]) : ptx::addc(x[n - 1], y[n - 1]);
+      ptx::addc(0, 0);
       return 0;
     }
     return SUBTRACT ? ptx::subc(0, 0) : ptx::addc(0, 0);
@@ -327,7 +326,7 @@ public:
 
   static DEVICE_INLINE void mul_n(uint32_t* acc, const uint32_t* a, uint32_t bi, size_t n = TLC)
   {
-#pragma unroll
+    UNROLL
     for (size_t i = 0; i < n; i += 2) {
       acc[i] = ptx::mul_lo(a[i], bi);
       acc[i + 1] = ptx::mul_hi(a[i], bi);
@@ -336,7 +335,7 @@ public:
 
   static DEVICE_INLINE void mul_n_msb(uint32_t* acc, const uint32_t* a, uint32_t bi, size_t n = TLC, size_t start_i = 0)
   {
-#pragma unroll
+    UNROLL
     for (size_t i = start_i; i < n; i += 2) {
       acc[i] = ptx::mul_lo(a[i], bi);
       acc[i + 1] = ptx::mul_hi(a[i], bi);
@@ -344,14 +343,14 @@ public:
   }
 
   template <bool CARRY_IN = false>
-  static __device__ __forceinline__ void
+  static DEVICE_INLINE void
   cmad_n(uint32_t* acc, const uint32_t* a, uint32_t bi, size_t n = TLC, uint32_t optional_carry = 0)
   {
     if (CARRY_IN) ptx::add_cc(UINT32_MAX, optional_carry);
     acc[0] = CARRY_IN ? ptx::madc_lo_cc(a[0], bi, acc[0]) : ptx::mad_lo_cc(a[0], bi, acc[0]);
     acc[1] = ptx::madc_hi_cc(a[0], bi, acc[1]);
 
-#pragma unroll
+    UNROLL
     for (size_t i = 2; i < n; i += 2) {
       acc[i] = ptx::madc_lo_cc(a[i], bi, acc[i]);
       acc[i + 1] = ptx::madc_hi_cc(a[i], bi, acc[i + 1]);
@@ -359,7 +358,7 @@ public:
   }
 
   template <bool EVEN_PHASE>
-  static __device__ __forceinline__ void cmad_n_msb(uint32_t* acc, const uint32_t* a, uint32_t bi, size_t n = TLC)
+  static DEVICE_INLINE void cmad_n_msb(uint32_t* acc, const uint32_t* a, uint32_t bi, size_t n = TLC)
   {
     if (EVEN_PHASE) {
       acc[0] = ptx::mad_lo_cc(a[0], bi, acc[0]);
@@ -368,14 +367,14 @@ public:
       acc[1] = ptx::mad_hi_cc(a[0], bi, acc[1]);
     }
 
-#pragma unroll
+    UNROLL
     for (size_t i = 2; i < n; i += 2) {
       acc[i] = ptx::madc_lo_cc(a[i], bi, acc[i]);
       acc[i + 1] = ptx::madc_hi_cc(a[i], bi, acc[i + 1]);
     }
   }
 
-  static __device__ __forceinline__ void cmad_n_lsb(uint32_t* acc, const uint32_t* a, uint32_t bi, size_t n = TLC)
+  static DEVICE_INLINE void cmad_n_lsb(uint32_t* acc, const uint32_t* a, uint32_t bi, size_t n = TLC)
   {
     if (n > 1)
       acc[0] = ptx::mad_lo_cc(a[0], bi, acc[0]);
@@ -383,7 +382,7 @@ public:
       acc[0] = ptx::mad_lo(a[0], bi, acc[0]);
 
     size_t i;
-#pragma unroll
+    UNROLL
     for (i = 1; i < n - 1; i += 2) {
       acc[i] = ptx::madc_hi_cc(a[i - 1], bi, acc[i]);
       if (i == n - 2)
@@ -395,7 +394,7 @@ public:
   }
 
   template <bool CARRY_OUT = false, bool CARRY_IN = false>
-  static __device__ __forceinline__ uint32_t mad_row(
+  static DEVICE_INLINE uint32_t mad_row(
     uint32_t* odd,
     uint32_t* even,
     const uint32_t* a,
@@ -420,8 +419,7 @@ public:
   }
 
   template <bool EVEN_PHASE>
-  static __device__ __forceinline__ void
-  mad_row_msb(uint32_t* odd, uint32_t* even, const uint32_t* a, uint32_t bi, size_t n = TLC)
+  static DEVICE_INLINE void mad_row_msb(uint32_t* odd, uint32_t* even, const uint32_t* a, uint32_t bi, size_t n = TLC)
   {
     cmad_n_msb<!EVEN_PHASE>(odd, EVEN_PHASE ? a : (a + 1), bi, n - 2);
     odd[EVEN_PHASE ? (n - 1) : (n - 2)] = ptx::madc_lo_cc(a[n - 1], bi, 0);
@@ -430,8 +428,7 @@ public:
     odd[EVEN_PHASE ? n : (n - 1)] = ptx::addc(odd[EVEN_PHASE ? n : (n - 1)], 0);
   }
 
-  static __device__ __forceinline__ void
-  mad_row_lsb(uint32_t* odd, uint32_t* even, const uint32_t* a, uint32_t bi, size_t n = TLC)
+  static DEVICE_INLINE void mad_row_lsb(uint32_t* odd, uint32_t* even, const uint32_t* a, uint32_t bi, size_t n = TLC)
   {
     // bi here is constant so we can do a compile-time check for zero (which does happen once for bls12-381 scalar field
     // modulus)
@@ -442,12 +439,12 @@ public:
     return;
   }
 
-  static __device__ __forceinline__ uint32_t
+  static DEVICE_INLINE uint32_t
   mul_n_and_add(uint32_t* acc, const uint32_t* a, uint32_t bi, uint32_t* extra, size_t n = (TLC >> 1))
   {
     acc[0] = ptx::mad_lo_cc(a[0], bi, extra[0]);
 
-#pragma unroll
+    UNROLL
     for (size_t i = 1; i < n - 1; i += 2) {
       acc[i] = ptx::madc_hi_cc(a[i - 1], bi, extra[i]);
       acc[i + 1] = ptx::madc_lo_cc(a[i + 1], bi, extra[i + 1]);
@@ -470,70 +467,86 @@ public:
    * \cdot b_0}{2^{32}}} + \dots + \floor{\frac{a_0 \cdot b_{TLC - 2}}{2^{32}}}) \leq 2^{64} + 2\cdot 2^{96} + \dots +
    * (TLC - 2) \cdot 2^{32(TLC - 1)} + (TLC - 1) \cdot 2^{32(TLC - 1)} \leq 2(TLC - 1) \cdot 2^{32(TLC - 1)}\f$.
    */
-  static __device__ __forceinline__ void
-  multiply_msb_raw_device(const ff_storage& as, const ff_storage& bs, ff_wide_storage& rs)
+  static DEVICE_INLINE void multiply_msb_raw_device(const ff_storage& as, const ff_storage& bs, ff_wide_storage& rs)
   {
-    const uint32_t* a = as.limbs;
-    const uint32_t* b = bs.limbs;
-    uint32_t* even = rs.limbs;
-    __align__(16) uint32_t odd[2 * TLC - 2];
+    if constexpr (TLC > 1) {
+      const uint32_t* a = as.limbs;
+      const uint32_t* b = bs.limbs;
+      uint32_t* even = rs.limbs;
+      __align__(16) uint32_t odd[2 * TLC - 2];
 
-    even[TLC - 1] = ptx::mul_hi(a[TLC - 2], b[0]);
-    odd[TLC - 2] = ptx::mul_lo(a[TLC - 1], b[0]);
-    odd[TLC - 1] = ptx::mul_hi(a[TLC - 1], b[0]);
-    size_t i;
-#pragma unroll
-    for (i = 2; i < TLC - 1; i += 2) {
-      mad_row_msb<true>(&even[TLC - 2], &odd[TLC - 2], &a[TLC - i - 1], b[i - 1], i + 1);
-      mad_row_msb<false>(&odd[TLC - 2], &even[TLC - 2], &a[TLC - i - 2], b[i], i + 2);
+      even[TLC - 1] = ptx::mul_hi(a[TLC - 2], b[0]);
+      odd[TLC - 2] = ptx::mul_lo(a[TLC - 1], b[0]);
+      odd[TLC - 1] = ptx::mul_hi(a[TLC - 1], b[0]);
+      size_t i;
+      UNROLL
+      for (i = 2; i < TLC - 1; i += 2) {
+        mad_row_msb<true>(&even[TLC - 2], &odd[TLC - 2], &a[TLC - i - 1], b[i - 1], i + 1);
+        mad_row_msb<false>(&odd[TLC - 2], &even[TLC - 2], &a[TLC - i - 2], b[i], i + 2);
+      }
+      mad_row(&even[TLC], &odd[TLC - 2], a, b[TLC - 1]);
+
+      // merge |even| and |odd|
+      ptx::add_cc(even[TLC - 1], odd[TLC - 2]);
+      for (i = TLC - 1; i < 2 * TLC - 2; i++)
+        even[i + 1] = ptx::addc_cc(even[i + 1], odd[i]);
+      even[i + 1] = ptx::addc(even[i + 1], 0);
+    } else {
+      multiply_raw_device(as, bs, rs);
     }
-    mad_row(&even[TLC], &odd[TLC - 2], a, b[TLC - 1]);
-
-    // merge |even| and |odd|
-    ptx::add_cc(even[TLC - 1], odd[TLC - 2]);
-    for (i = TLC - 1; i < 2 * TLC - 2; i++)
-      even[i + 1] = ptx::addc_cc(even[i + 1], odd[i]);
-    even[i + 1] = ptx::addc(even[i + 1], 0);
   }
 
   /**
-   * A function that computes the low half of the fused multiply-and-add \f$ rs = as \cdot bs + cs \f$.
+   * A function that computes the low half of the fused multiply-and-add \f$ rs = as \cdot bs + cs \f$ where
+   * \f$ bs = 2^{32*nof_limbs} \f$.
    *
    * For efficiency, this method does not include terms that are too large. Namely, limb product \f$ a_i \cdot b_j \f$
    * is excluded if \f$ i + j > TLC - 1 \f$ and only the lower half is included if \f$ i + j = TLC - 1 \f$. All other
    * limb products are included.
    */
-  static __device__ __forceinline__ void
-  multiply_and_add_lsb_raw_device(const ff_storage& as, const ff_storage& bs, ff_storage& cs, ff_storage& rs)
+  static DEVICE_INLINE void
+  multiply_and_add_lsb_neg_modulus_raw_device(const ff_storage& as, ff_storage& cs, ff_storage& rs)
   {
+    ff_storage bs = get_neg_modulus();
     const uint32_t* a = as.limbs;
     const uint32_t* b = bs.limbs;
+    uint32_t* c = cs.limbs;
     uint32_t* even = rs.limbs;
-    __align__(16) uint32_t odd[TLC - 1];
-    size_t i;
-    // `b[0]` is \f$ 2^{32} \f$ minus the last limb of prime modulus. Because most scalar (and some base) primes
-    // are necessarily NTT-friendly, `b[0]` often turns out to be \f$ 2^{32} - 1 \f$. This actually leads to
-    // less efficient SASS generated by nvcc, so this case needed separate handling.
-    if (b[0] == UINT32_MAX) {
-      add_sub_u32_device<true, false>(cs.limbs, a, even, TLC);
-      for (i = 0; i < TLC - 1; i++)
-        odd[i] = a[i];
-    } else {
-      mul_n_and_add(even, a, b[0], cs.limbs, TLC);
-      mul_n(odd, a + 1, b[0], TLC - 1);
-    }
-    mad_row_lsb(&even[2], &odd[0], a, b[1], TLC - 1);
-#pragma unroll
-    for (i = 2; i < TLC - 1; i += 2) {
-      mad_row_lsb(&odd[i], &even[i], a, b[i], TLC - i);
-      mad_row_lsb(&even[i + 2], &odd[i], a, b[i + 1], TLC - i - 1);
-    }
 
-    // merge |even| and |odd|
-    even[1] = ptx::add_cc(even[1], odd[0]);
-    for (i = 1; i < TLC - 2; i++)
-      even[i + 1] = ptx::addc_cc(even[i + 1], odd[i]);
-    even[i + 1] = ptx::addc(even[i + 1], odd[i]);
+    if constexpr (TLC > 2) {
+      __align__(16) uint32_t odd[TLC - 1];
+      size_t i;
+      // `b[0]` is \f$ 2^{32} \f$ minus the last limb of prime modulus. Because most scalar (and some base) primes
+      // are necessarily NTT-friendly, `b[0]` often turns out to be \f$ 2^{32} - 1 \f$. This actually leads to
+      // less efficient SASS generated by nvcc, so this case needed separate handling.
+      if (b[0] == UINT32_MAX) {
+        add_sub_u32_device<true, false>(c, a, even, TLC);
+        for (i = 0; i < TLC - 1; i++)
+          odd[i] = a[i];
+      } else {
+        mul_n_and_add(even, a, b[0], c, TLC);
+        mul_n(odd, a + 1, b[0], TLC - 1);
+      }
+      mad_row_lsb(&even[2], &odd[0], a, b[1], TLC - 1);
+      UNROLL
+      for (i = 2; i < TLC - 1; i += 2) {
+        mad_row_lsb(&odd[i], &even[i], a, b[i], TLC - i);
+        mad_row_lsb(&even[i + 2], &odd[i], a, b[i + 1], TLC - i - 1);
+      }
+
+      // merge |even| and |odd|
+      even[1] = ptx::add_cc(even[1], odd[0]);
+      for (i = 1; i < TLC - 2; i++)
+        even[i + 1] = ptx::addc_cc(even[i + 1], odd[i]);
+      even[i + 1] = ptx::addc(even[i + 1], odd[i]);
+    } else if (TLC == 2) {
+      even[0] = ptx::mad_lo(a[0], b[0], c[0]);
+      even[1] = ptx::mad_hi(a[0], b[0], c[0]);
+      even[1] = ptx::mad_lo(a[0], b[1], even[1]);
+      even[1] = ptx::mad_lo(a[1], b[0], even[1]);
+    } else if (TLC == 1) {
+      even[0] = ptx::mad_lo(a[0], b[0], c[0]);
+    }
   }
 
   /**
@@ -545,7 +558,7 @@ public:
    * that the top bit of \f$ a_{hi} \f$ and \f$ b_{hi} \f$ are unset. This ensures correctness by allowing to keep the
    * result inside TLC limbs and ignore the carries from the highest limb.
    */
-  static __device__ __forceinline__ void
+  static DEVICE_INLINE void
   multiply_and_add_short_raw_device(const uint32_t* a, const uint32_t* b, uint32_t* even, uint32_t* in1, uint32_t* in2)
   {
     __align__(16) uint32_t odd[TLC - 2];
@@ -553,7 +566,7 @@ public:
     uint32_t carry = mul_n_and_add(odd, a + 1, b[0], &in2[1]);
 
     size_t i;
-#pragma unroll
+    UNROLL
     for (i = 2; i < ((TLC >> 1) - 1); i += 2) {
       carry = mad_row<true, false>(
         &even[i], &odd[i - 2], a, b[i - 1], TLC >> 1, in1[(TLC >> 1) + i - 2], in1[(TLC >> 1) + i - 1], carry);
@@ -574,7 +587,7 @@ public:
    * This method multiplies `a` and `b` and writes the result into `even`. It assumes that `a` and `b` are TLC/2 limbs
    * long. The usual schoolbook algorithm is used.
    */
-  static __device__ __forceinline__ void multiply_short_raw_device(const uint32_t* a, const uint32_t* b, uint32_t* even)
+  static DEVICE_INLINE void multiply_short_raw_device(const uint32_t* a, const uint32_t* b, uint32_t* even)
   {
     __align__(16) uint32_t odd[TLC - 2];
     mul_n(even, a, b[0], TLC >> 1);
@@ -582,7 +595,7 @@ public:
     mad_row(&even[2], &odd[0], a, b[1], TLC >> 1);
 
     size_t i;
-#pragma unroll
+    UNROLL
     for (i = 2; i < ((TLC >> 1) - 1); i += 2) {
       mad_row(&odd[i], &even[i], a, b[i], TLC >> 1);
       mad_row(&even[i + 2], &odd[i], a, b[i + 1], TLC >> 1);
@@ -606,29 +619,47 @@ public:
     const uint32_t* a = as.limbs;
     const uint32_t* b = bs.limbs;
     uint32_t* r = rs.limbs;
-    // Next two lines multiply high and low halves of operands (\f$ a_{lo} \cdot b_{lo}; a_{hi} \cdot b_{hi} \$f) and
-    // write the results into `r`.
-    multiply_short_raw_device(a, b, r);
-    multiply_short_raw_device(&a[TLC >> 1], &b[TLC >> 1], &r[TLC]);
-    __align__(16) uint32_t middle_part[TLC];
-    __align__(16) uint32_t diffs[TLC];
-    // Differences of halves \f$ a_{hi} - a_{lo}; b_{lo} - b_{hi} \$f are written into `diffs`, signs written to
-    // `carry1` and `carry2`.
-    uint32_t carry1 = add_sub_u32_device<true, true>(&a[TLC >> 1], a, diffs);
-    uint32_t carry2 = add_sub_u32_device<true, true>(b, &b[TLC >> 1], &diffs[TLC >> 1]);
-    // Compute the "middle part" of Karatsuba: \f$ a_{lo} \cdot b_{hi} + b_{lo} \cdot a_{hi} \f$.
-    // This is where the assumption about unset high bit of `a` and `b` is relevant.
-    multiply_and_add_short_raw_device(diffs, &diffs[TLC >> 1], middle_part, r, &r[TLC]);
-    // Corrections that need to be performed when differences are negative.
-    // Again, carry doesn't need to be propagated due to unset high bits of `a` and `b`.
-    if (carry1) add_sub_u32_device<true, false>(&middle_part[TLC >> 1], &diffs[TLC >> 1], &middle_part[TLC >> 1]);
-    if (carry2) add_sub_u32_device<true, false>(&middle_part[TLC >> 1], diffs, &middle_part[TLC >> 1]);
-    // Now that middle part is fully correct, it can be added to the result.
-    add_sub_u32_device<false, true>(&r[TLC >> 1], middle_part, &r[TLC >> 1], TLC);
+    if constexpr (TLC > 2) {
+      // Next two lines multiply high and low halves of operands (\f$ a_{lo} \cdot b_{lo}; a_{hi} \cdot b_{hi} \$f) and
+      // write the results into `r`.
+      multiply_short_raw_device(a, b, r);
+      multiply_short_raw_device(&a[TLC >> 1], &b[TLC >> 1], &r[TLC]);
+      __align__(16) uint32_t middle_part[TLC];
+      __align__(16) uint32_t diffs[TLC];
+      // Differences of halves \f$ a_{hi} - a_{lo}; b_{lo} - b_{hi} \$f are written into `diffs`, signs written to
+      // `carry1` and `carry2`.
+      uint32_t carry1 = add_sub_u32_device<true, true>(&a[TLC >> 1], a, diffs);
+      uint32_t carry2 = add_sub_u32_device<true, true>(b, &b[TLC >> 1], &diffs[TLC >> 1]);
+      // Compute the "middle part" of Karatsuba: \f$ a_{lo} \cdot b_{hi} + b_{lo} \cdot a_{hi} \f$.
+      // This is where the assumption about unset high bit of `a` and `b` is relevant.
+      multiply_and_add_short_raw_device(diffs, &diffs[TLC >> 1], middle_part, r, &r[TLC]);
+      // Corrections that need to be performed when differences are negative.
+      // Again, carry doesn't need to be propagated due to unset high bits of `a` and `b`.
+      if (carry1) add_sub_u32_device<true, false>(&middle_part[TLC >> 1], &diffs[TLC >> 1], &middle_part[TLC >> 1]);
+      if (carry2) add_sub_u32_device<true, false>(&middle_part[TLC >> 1], diffs, &middle_part[TLC >> 1]);
+      // Now that middle part is fully correct, it can be added to the result.
+      add_sub_u32_device<false, true>(&r[TLC >> 1], middle_part, &r[TLC >> 1], TLC);
 
-    // Carry from adding middle part has to be propagated to the highest limb.
-    for (size_t i = TLC + (TLC >> 1); i < 2 * TLC; i++)
-      r[i] = ptx::addc_cc(r[i], 0);
+      // Carry from adding middle part has to be propagated to the highest limb.
+      for (size_t i = TLC + (TLC >> 1); i < 2 * TLC; i++)
+        r[i] = ptx::addc_cc(r[i], 0);
+    } else if (TLC == 2) {
+      __align__(8) uint32_t odd[2];
+      r[0] = ptx::mul_lo(a[0], b[0]);
+      r[1] = ptx::mul_hi(a[0], b[0]);
+      r[2] = ptx::mul_lo(a[1], b[1]);
+      r[3] = ptx::mul_hi(a[1], b[1]);
+      odd[0] = ptx::mul_lo(a[0], b[1]);
+      odd[1] = ptx::mul_hi(a[0], b[1]);
+      odd[0] = ptx::mad_lo(a[1], b[0], odd[0]);
+      odd[1] = ptx::mad_hi(a[1], b[0], odd[1]);
+      r[1] = ptx::add_cc(r[1], odd[0]);
+      r[2] = ptx::addc_cc(r[2], odd[1]);
+      r[3] = ptx::addc(r[3], 0);
+    } else if (TLC == 1) {
+      r[0] = ptx::mul_lo(a[0], b[0]);
+      r[1] = ptx::mul_hi(a[0], b[0]);
+    }
   }
 
   static HOST_INLINE void multiply_raw_host(const ff_storage& as, const ff_storage& bs, ff_wide_storage& rs)
@@ -654,13 +685,13 @@ public:
   }
 
   static HOST_DEVICE_INLINE void
-  multiply_and_add_lsb_raw(const ff_storage& as, const ff_storage& bs, ff_storage& cs, ff_storage& rs)
+  multiply_and_add_lsb_neg_modulus_raw(const ff_storage& as, ff_storage& cs, ff_storage& rs)
   {
 #ifdef __CUDA_ARCH__
-    return multiply_and_add_lsb_raw_device(as, bs, cs, rs);
+    return multiply_and_add_lsb_neg_modulus_raw_device(as, cs, rs);
 #else
     Wide r_wide = {};
-    multiply_raw_host(as, bs, r_wide.limbs_storage);
+    multiply_raw_host(as, get_neg_modulus(), r_wide.limbs_storage);
     Field r = Wide::get_lower(r_wide);
     add_limbs<false>(cs, r.limbs_storage, rs);
 #endif
@@ -791,7 +822,7 @@ public:
     Field xs_lo = Wide::get_lower(xs);
     // Here we need to compute the lsb of `xs - l \cdot p` and to make use of fused multiply-and-add, we rewrite it as
     // `xs + l \cdot (2^{32 \cdot TLC}-p)` which is the same as original (up to higher limbs which we don't care about).
-    multiply_and_add_lsb_raw(l_hi.limbs_storage, get_neg_modulus(), xs_lo.limbs_storage, r.limbs_storage);
+    multiply_and_add_lsb_neg_modulus_raw(l_hi.limbs_storage, xs_lo.limbs_storage, r.limbs_storage);
     ff_storage r_reduced = {};
     uint32_t carry;
     // As mentioned, either 2 or 1 reduction can be performed depending on the field in question.
@@ -817,7 +848,7 @@ public:
     const uint32_t* x = xs.limbs_storage.limbs;
     const uint32_t* y = ys.limbs_storage.limbs;
     uint32_t limbs_or = x[0] ^ y[0];
-#pragma unroll
+    UNROLL
     for (unsigned i = 1; i < TLC; i++)
       limbs_or |= x[i] ^ y[i];
     return limbs_or == 0;
@@ -836,7 +867,7 @@ public:
     Field mul = multiplier;
     static bool is_u32 = true;
 #ifdef __CUDA_ARCH__
-#pragma unroll
+    UNROLL
 #endif
     for (unsigned i = 1; i < TLC; i++)
       is_u32 &= (mul.limbs_storage.limbs[i] == 0);
@@ -852,7 +883,7 @@ public:
     T temp = xs;
     bool is_zero = true;
 #ifdef __CUDA_ARCH__
-#pragma unroll
+    UNROLL
 #endif
     for (unsigned i = 0; i < 32; i++) {
       if (multiplier & (1 << i)) {
@@ -895,21 +926,24 @@ public:
     return rs;
   }
 
+  // Assumes the number is even!
   template <unsigned MODULUS_MULTIPLE = 1>
   static constexpr HOST_DEVICE_INLINE Field div2(const Field& xs)
   {
     const uint32_t* x = xs.limbs_storage.limbs;
     Field rs = {};
     uint32_t* r = rs.limbs_storage.limbs;
+    if constexpr (TLC > 1) {
 #ifdef __CUDA_ARCH__
-#pragma unroll
+      UNROLL
 #endif
-    for (unsigned i = 0; i < TLC - 1; i++) {
+      for (unsigned i = 0; i < TLC - 1; i++) {
 #ifdef __CUDA_ARCH__
-      r[i] = __funnelshift_rc(x[i], x[i + 1], 1);
+        r[i] = __funnelshift_rc(x[i], x[i + 1], 1);
 #else
-      r[i] = (x[i] >> 1) | (x[i + 1] << 31);
+        r[i] = (x[i] >> 1) | (x[i + 1] << 31);
 #endif
+      }
     }
     r[TLC - 1] = x[TLC - 1] >> 1;
     return sub_modulus<MODULUS_MULTIPLE>(rs);
@@ -969,4 +1003,13 @@ struct std::hash<Field<CONFIG>> {
       hash ^= std::hash<uint32_t>()(key.limbs_storage.limbs[i]) + 0x9e3779b9 + (hash << 6) + (hash >> 2);
     return hash;
   }
+};
+
+template <class CONFIG>
+struct SharedMemory<Field<CONFIG>> {
+  __device__ Field<CONFIG>* getPointer()
+  {
+    extern __shared__ Field<CONFIG> s_scalar_[];
+    return s_scalar_;
+  }
 };

icicle/include/fields/field_config.cuh

@@ -0,0 +1,51 @@
+#pragma once
+#ifndef FIELD_CONFIG_H
+#define FIELD_CONFIG_H
+
+#include "fields/id.h"
+#include "fields/field.cuh"
+
+#if FIELD_ID == BN254
+#include "fields/snark_fields/bn254_scalar.cuh"
+using bn254::fp_config;
+#elif FIELD_ID == BLS12_381
+#include "fields/snark_fields/bls12_381_scalar.cuh"
+using bls12_381::fp_config;
+#elif FIELD_ID == BLS12_377
+#include "fields/snark_fields/bls12_377_scalar.cuh"
+using bls12_377::fp_config;
+#elif FIELD_ID == BW6_761
+#include "fields/snark_fields/bls12_377_base.cuh"
+typedef bls12_377::fq_config fp_config;
+#elif FIELD_ID == GRUMPKIN
+#include "fields/snark_fields/bn254_base.cuh"
+typedef bn254::fq_config fp_config;
+
+#elif FIELD_ID == BABY_BEAR
+#include "fields/stark_fields/baby_bear.cuh"
+using baby_bear::fp_config;
+#ifdef EXT_FIELD
+#include "fields/quartic_extension.cuh"
+#endif
+#endif
+
+/**
+ * @namespace field_config
+ * Namespace with type definitions for finite fields. Here, concrete types are created in accordance
+ * with the `-DFIELD` env variable passed during build.
+ */
+namespace field_config {
+  /**
+   * Scalar field. Is always a prime field.
+   */
+  typedef Field<fp_config> scalar_t;
+
+#ifdef EXT_FIELD
+  /**
+   * Extension field of `scalar_t` enabled if `-DEXT_FIELD` env variable is.
+   */
+  typedef ExtensionField<fp_config> extension_t;
+#endif
+} // namespace field_config
+
+#endif

icicle/include/fields/host_math.cuh

@@ -4,7 +4,7 @@
 
 #include <cstdint>
 #include <cuda_runtime.h>
-
+#include "gpu-utils/modifiers.cuh"
 namespace host_math {
 
   // return x + y with uint32_t operands
@@ -67,9 +67,9 @@ namespace host_math {
   struct carry_chain {
     unsigned index;
 
-    constexpr __host__ __forceinline__ carry_chain() : index(0) {}
+    constexpr HOST_INLINE carry_chain() : index(0) {}
 
-    __host__ __forceinline__ uint32_t add(const uint32_t x, const uint32_t y, uint32_t& carry)
+    HOST_INLINE uint32_t add(const uint32_t x, const uint32_t y, uint32_t& carry)
     {
       index++;
       if (index == 1 && OPS_COUNT == 1 && !CARRY_IN && !CARRY_OUT)
@@ -82,7 +82,7 @@ namespace host_math {
         return host_math::addc(x, y, carry);
     }
 
-    __host__ __forceinline__ uint32_t sub(const uint32_t x, const uint32_t y, uint32_t& carry)
+    HOST_INLINE uint32_t sub(const uint32_t x, const uint32_t y, uint32_t& carry)
     {
       index++;
       if (index == 1 && OPS_COUNT == 1 && !CARRY_IN && !CARRY_OUT)

icicle/include/fields/id.h

@@ -0,0 +1,13 @@
+#pragma once
+#ifndef FIELD_ID_H
+#define FIELD_ID_H
+
+#define BN254     1
+#define BLS12_381 2
+#define BLS12_377 3
+#define BW6_761   4
+#define GRUMPKIN  5
+
+#define BABY_BEAR 1001
+
+#endif

icicle/include/fields/quadratic_extension.cuh

@@ -1,15 +1,15 @@
 #pragma once
 
 #include "field.cuh"
-
-#define HOST_INLINE        __host__ __forceinline__
-#define DEVICE_INLINE      __device__ __forceinline__
-#define HOST_DEVICE_INLINE __host__ __device__ __forceinline__
+#include "gpu-utils/modifiers.cuh"
+#include "gpu-utils/sharedmem.cuh"
 
 template <typename CONFIG>
 class ExtensionField
 {
 private:
+  friend Field<CONFIG>;
+
   typedef typename Field<CONFIG>::Wide FWide;
 
   struct ExtensionWide {
@@ -50,6 +50,12 @@ public:
 
   static HOST_INLINE ExtensionField rand_host() { return ExtensionField{FF::rand_host(), FF::rand_host()}; }
 
+  static void RandHostMany(ExtensionField* out, int size)
+  {
+    for (int i = 0; i < size; i++)
+      out[i] = rand_host();
+  }
+
   template <unsigned REDUCTION_SIZE = 1>
   static constexpr HOST_DEVICE_INLINE ExtensionField sub_modulus(const ExtensionField& xs)
   {
@@ -72,15 +78,47 @@ public:
     return ExtensionField{xs.real - ys.real, xs.imaginary - ys.imaginary};
   }
 
+  friend HOST_DEVICE_INLINE ExtensionField operator+(FF xs, const ExtensionField& ys)
+  {
+    return ExtensionField{xs + ys.real, ys.imaginary};
+  }
+
+  friend HOST_DEVICE_INLINE ExtensionField operator-(FF xs, const ExtensionField& ys)
+  {
+    return ExtensionField{xs - ys.real, FF::neg(ys.imaginary)};
+  }
+
+  friend HOST_DEVICE_INLINE ExtensionField operator+(ExtensionField xs, const FF& ys)
+  {
+    return ExtensionField{xs.real + ys, xs.imaginary};
+  }
+
+  friend HOST_DEVICE_INLINE ExtensionField operator-(ExtensionField xs, const FF& ys)
+  {
+    return ExtensionField{xs.real - ys, xs.imaginary};
+  }
+
   template <unsigned MODULUS_MULTIPLE = 1>
   static constexpr HOST_DEVICE_INLINE ExtensionWide mul_wide(const ExtensionField& xs, const ExtensionField& ys)
   {
     FWide real_prod = FF::mul_wide(xs.real, ys.real);
     FWide imaginary_prod = FF::mul_wide(xs.imaginary, ys.imaginary);
     FWide prod_of_sums = FF::mul_wide(xs.real + xs.imaginary, ys.real + ys.imaginary);
-    FWide i_sq_times_im = FF::template mul_unsigned<CONFIG::i_squared>(imaginary_prod);
-    i_sq_times_im = CONFIG::i_squared_is_negative ? FWide::neg(i_sq_times_im) : i_sq_times_im;
-    return ExtensionWide{real_prod + i_sq_times_im, prod_of_sums - real_prod - imaginary_prod};
+    FWide nonresidue_times_im = FF::template mul_unsigned<CONFIG::nonresidue>(imaginary_prod);
+    nonresidue_times_im = CONFIG::nonresidue_is_negative ? FWide::neg(nonresidue_times_im) : nonresidue_times_im;
+    return ExtensionWide{real_prod + nonresidue_times_im, prod_of_sums - real_prod - imaginary_prod};
+  }
+
+  template <unsigned MODULUS_MULTIPLE = 1>
+  static constexpr HOST_DEVICE_INLINE ExtensionWide mul_wide(const ExtensionField& xs, const FF& ys)
+  {
+    return ExtensionWide{FF::mul_wide(xs.real, ys), FF::mul_wide(xs.imaginary, ys)};
+  }
+
+  template <unsigned MODULUS_MULTIPLE = 1>
+  static constexpr HOST_DEVICE_INLINE ExtensionWide mul_wide(const FF& xs, const ExtensionField& ys)
+  {
+    return mul_wide(ys, xs);
   }
 
   template <unsigned MODULUS_MULTIPLE = 1>
@@ -90,7 +128,8 @@ public:
       FF::template reduce<MODULUS_MULTIPLE>(xs.real), FF::template reduce<MODULUS_MULTIPLE>(xs.imaginary)};
   }
 
-  friend HOST_DEVICE_INLINE ExtensionField operator*(const ExtensionField& xs, const ExtensionField& ys)
+  template <class T1, class T2>
+  friend HOST_DEVICE_INLINE ExtensionField operator*(const T1& xs, const T2& ys)
   {
     ExtensionWide xy = mul_wide(xs, ys);
     return reduce(xy);
@@ -114,9 +153,9 @@ public:
     FF imaginary_prod = FF::template mul_const<mul_imaginary>(xs_imaginary);
     FF re_im = FF::template mul_const<mul_real>(xs_imaginary);
     FF im_re = FF::template mul_const<mul_imaginary>(xs_real);
-    FF i_sq_times_im = FF::template mul_unsigned<CONFIG::i_squared>(imaginary_prod);
-    i_sq_times_im = CONFIG::i_squared_is_negative ? FF::neg(i_sq_times_im) : i_sq_times_im;
-    return ExtensionField{real_prod + i_sq_times_im, re_im + im_re};
+    FF nonresidue_times_im = FF::template mul_unsigned<CONFIG::nonresidue>(imaginary_prod);
+    nonresidue_times_im = CONFIG::nonresidue_is_negative ? FF::neg(nonresidue_times_im) : nonresidue_times_im;
+    return ExtensionField{real_prod + nonresidue_times_im, re_im + im_re};
   }
 
   template <uint32_t multiplier, unsigned REDUCTION_SIZE = 1>
@@ -145,14 +184,23 @@ public:
     return ExtensionField{FF::neg(xs.real), FF::neg(xs.imaginary)};
   }
 
-  // inverse assumes that xs is nonzero
+  // inverse of zero is set to be zero which is what we want most of the time
   static constexpr HOST_DEVICE_INLINE ExtensionField inverse(const ExtensionField& xs)
   {
     ExtensionField xs_conjugate = {xs.real, FF::neg(xs.imaginary)};
-    FF i_sq_times_im = FF::template mul_unsigned<CONFIG::i_squared>(FF::sqr(xs.imaginary));
-    i_sq_times_im = CONFIG::i_squared_is_negative ? FF::neg(i_sq_times_im) : i_sq_times_im;
+    FF nonresidue_times_im = FF::template mul_unsigned<CONFIG::nonresidue>(FF::sqr(xs.imaginary));
+    nonresidue_times_im = CONFIG::nonresidue_is_negative ? FF::neg(nonresidue_times_im) : nonresidue_times_im;
     // TODO: wide here
-    FF xs_norm_squared = FF::sqr(xs.real) - i_sq_times_im;
+    FF xs_norm_squared = FF::sqr(xs.real) - nonresidue_times_im;
     return xs_conjugate * ExtensionField{FF::inverse(xs_norm_squared), FF::zero()};
   }
+};
+
+template <class CONFIG>
+struct SharedMemory<ExtensionField<CONFIG>> {
+  __device__ ExtensionField<CONFIG>* getPointer()
+  {
+    extern __shared__ ExtensionField<CONFIG> s_ext2_scalar_[];
+    return s_ext2_scalar_;
+  }
 };

icicle/include/fields/quartic_extension.cuh

@@ -0,0 +1,257 @@
+#pragma once
+
+#include "field.cuh"
+#include "gpu-utils/modifiers.cuh"
+#include "gpu-utils/sharedmem.cuh"
+
+template <typename CONFIG>
+class ExtensionField
+{
+private:
+  typedef typename Field<CONFIG>::Wide FWide;
+
+  struct ExtensionWide {
+    FWide real;
+    FWide im1;
+    FWide im2;
+    FWide im3;
+
+    friend HOST_DEVICE_INLINE ExtensionWide operator+(ExtensionWide xs, const ExtensionWide& ys)
+    {
+      return ExtensionWide{xs.real + ys.real, xs.im1 + ys.im1, xs.im2 + ys.im2, xs.im3 + ys.im3};
+    }
+
+    friend HOST_DEVICE_INLINE ExtensionWide operator-(ExtensionWide xs, const ExtensionWide& ys)
+    {
+      return ExtensionWide{xs.real - ys.real, xs.im1 - ys.im1, xs.im2 - ys.im2, xs.im3 - ys.im3};
+    }
+  };
+
+public:
+  typedef Field<CONFIG> FF;
+  static constexpr unsigned TLC = 4 * CONFIG::limbs_count;
+
+  FF real;
+  FF im1;
+  FF im2;
+  FF im3;
+
+  static constexpr HOST_DEVICE_INLINE ExtensionField zero()
+  {
+    return ExtensionField{FF::zero(), FF::zero(), FF::zero(), FF::zero()};
+  }
+
+  static constexpr HOST_DEVICE_INLINE ExtensionField one()
+  {
+    return ExtensionField{FF::one(), FF::zero(), FF::zero(), FF::zero()};
+  }
+
+  static constexpr HOST_DEVICE_INLINE ExtensionField ToMontgomery(const ExtensionField& xs)
+  {
+    return ExtensionField{
+      xs.real * FF{CONFIG::montgomery_r}, xs.im1 * FF{CONFIG::montgomery_r}, xs.im2 * FF{CONFIG::montgomery_r},
+      xs.im3 * FF{CONFIG::montgomery_r}};
+  }
+
+  static constexpr HOST_DEVICE_INLINE ExtensionField FromMontgomery(const ExtensionField& xs)
+  {
+    return ExtensionField{
+      xs.real * FF{CONFIG::montgomery_r_inv}, xs.im1 * FF{CONFIG::montgomery_r_inv},
+      xs.im2 * FF{CONFIG::montgomery_r_inv}, xs.im3 * FF{CONFIG::montgomery_r_inv}};
+  }
+
+  static HOST_INLINE ExtensionField rand_host()
+  {
+    return ExtensionField{FF::rand_host(), FF::rand_host(), FF::rand_host(), FF::rand_host()};
+  }
+
+  static void RandHostMany(ExtensionField* out, int size)
+  {
+    for (int i = 0; i < size; i++)
+      out[i] = rand_host();
+  }
+
+  template <unsigned REDUCTION_SIZE = 1>
+  static constexpr HOST_DEVICE_INLINE ExtensionField sub_modulus(const ExtensionField& xs)
+  {
+    return ExtensionField{
+      FF::sub_modulus<REDUCTION_SIZE>(&xs.real), FF::sub_modulus<REDUCTION_SIZE>(&xs.im1),
+      FF::sub_modulus<REDUCTION_SIZE>(&xs.im2), FF::sub_modulus<REDUCTION_SIZE>(&xs.im3)};
+  }
+
+  friend std::ostream& operator<<(std::ostream& os, const ExtensionField& xs)
+  {
+    os << "{ Real: " << xs.real << " }; { Im1: " << xs.im1 << " }; { Im2: " << xs.im2 << " }; { Im3: " << xs.im3
+       << " };";
+    return os;
+  }
+
+  friend HOST_DEVICE_INLINE ExtensionField operator+(ExtensionField xs, const ExtensionField& ys)
+  {
+    return ExtensionField{xs.real + ys.real, xs.im1 + ys.im1, xs.im2 + ys.im2, xs.im3 + ys.im3};
+  }
+
+  friend HOST_DEVICE_INLINE ExtensionField operator-(ExtensionField xs, const ExtensionField& ys)
+  {
+    return ExtensionField{xs.real - ys.real, xs.im1 - ys.im1, xs.im2 - ys.im2, xs.im3 - ys.im3};
+  }
+
+  friend HOST_DEVICE_INLINE ExtensionField operator+(FF xs, const ExtensionField& ys)
+  {
+    return ExtensionField{xs + ys.real, ys.im1, ys.im2, ys.im3};
+  }
+
+  friend HOST_DEVICE_INLINE ExtensionField operator-(FF xs, const ExtensionField& ys)
+  {
+    return ExtensionField{xs - ys.real, FF::neg(ys.im1), FF::neg(ys.im2), FF::neg(ys.im3)};
+  }
+
+  friend HOST_DEVICE_INLINE ExtensionField operator+(ExtensionField xs, const FF& ys)
+  {
+    return ExtensionField{xs.real + ys, xs.im1, xs.im2, xs.im3};
+  }
+
+  friend HOST_DEVICE_INLINE ExtensionField operator-(ExtensionField xs, const FF& ys)
+  {
+    return ExtensionField{xs.real - ys, xs.im1, xs.im2, xs.im3};
+  }
+
+  template <unsigned MODULUS_MULTIPLE = 1>
+  static constexpr HOST_DEVICE_INLINE ExtensionWide mul_wide(const ExtensionField& xs, const ExtensionField& ys)
+  {
+    if (CONFIG::nonresidue_is_negative)
+      return ExtensionWide{
+        FF::mul_wide(xs.real, ys.real) -
+          FF::template mul_unsigned<CONFIG::nonresidue>(
+            FF::mul_wide(xs.im1, ys.im3) + FF::mul_wide(xs.im2, ys.im2) + FF::mul_wide(xs.im3, ys.im1)),
+        FF::mul_wide(xs.real, ys.im1) + FF::mul_wide(xs.im1, ys.real) -
+          FF::template mul_unsigned<CONFIG::nonresidue>(FF::mul_wide(xs.im2, ys.im3) + FF::mul_wide(xs.im3, ys.im2)),
+        FF::mul_wide(xs.real, ys.im2) + FF::mul_wide(xs.im1, ys.im1) + FF::mul_wide(xs.im2, ys.real) -
+          FF::template mul_unsigned<CONFIG::nonresidue>(FF::mul_wide(xs.im3, ys.im3)),
+        FF::mul_wide(xs.real, ys.im3) + FF::mul_wide(xs.im1, ys.im2) + FF::mul_wide(xs.im2, ys.im1) +
+          FF::mul_wide(xs.im3, ys.real)};
+    else
+      return ExtensionWide{
+        FF::mul_wide(xs.real, ys.real) +
+          FF::template mul_unsigned<CONFIG::nonresidue>(
+            FF::mul_wide(xs.im1, ys.im3) + FF::mul_wide(xs.im2, ys.im2) + FF::mul_wide(xs.im3, ys.im1)),
+        FF::mul_wide(xs.real, ys.im1) + FF::mul_wide(xs.im1, ys.real) +
+          FF::template mul_unsigned<CONFIG::nonresidue>(FF::mul_wide(xs.im2, ys.im3) + FF::mul_wide(xs.im3, ys.im2)),
+        FF::mul_wide(xs.real, ys.im2) + FF::mul_wide(xs.im1, ys.im1) + FF::mul_wide(xs.im2, ys.real) +
+          FF::template mul_unsigned<CONFIG::nonresidue>(FF::mul_wide(xs.im3, ys.im3)),
+        FF::mul_wide(xs.real, ys.im3) + FF::mul_wide(xs.im1, ys.im2) + FF::mul_wide(xs.im2, ys.im1) +
+          FF::mul_wide(xs.im3, ys.real)};
+  }
+
+  template <unsigned MODULUS_MULTIPLE = 1>
+  static constexpr HOST_DEVICE_INLINE ExtensionWide mul_wide(const ExtensionField& xs, const FF& ys)
+  {
+    return ExtensionWide{
+      FF::mul_wide(xs.real, ys), FF::mul_wide(xs.im1, ys), FF::mul_wide(xs.im2, ys), FF::mul_wide(xs.im3, ys)};
+  }
+
+  template <unsigned MODULUS_MULTIPLE = 1>
+  static constexpr HOST_DEVICE_INLINE ExtensionWide mul_wide(const FF& xs, const ExtensionField& ys)
+  {
+    return ExtensionWide{
+      FF::mul_wide(xs, ys.real), FF::mul_wide(xs, ys.im1), FF::mul_wide(xs, ys.im2), FF::mul_wide(xs, ys.im3)};
+  }
+
+  template <unsigned MODULUS_MULTIPLE = 1>
+  static constexpr HOST_DEVICE_INLINE ExtensionField reduce(const ExtensionWide& xs)
+  {
+    return ExtensionField{
+      FF::template reduce<MODULUS_MULTIPLE>(xs.real), FF::template reduce<MODULUS_MULTIPLE>(xs.im1),
+      FF::template reduce<MODULUS_MULTIPLE>(xs.im2), FF::template reduce<MODULUS_MULTIPLE>(xs.im3)};
+  }
+
+  template <class T1, class T2>
+  friend HOST_DEVICE_INLINE ExtensionField operator*(const T1& xs, const T2& ys)
+  {
+    ExtensionWide xy = mul_wide(xs, ys);
+    return reduce(xy);
+  }
+
+  friend HOST_DEVICE_INLINE bool operator==(const ExtensionField& xs, const ExtensionField& ys)
+  {
+    return (xs.real == ys.real) && (xs.im1 == ys.im1) && (xs.im2 == ys.im2) && (xs.im3 == ys.im3);
+  }
+
+  friend HOST_DEVICE_INLINE bool operator!=(const ExtensionField& xs, const ExtensionField& ys) { return !(xs == ys); }
+
+  template <uint32_t multiplier, unsigned REDUCTION_SIZE = 1>
+  static constexpr HOST_DEVICE_INLINE ExtensionField mul_unsigned(const ExtensionField& xs)
+  {
+    return {
+      FF::template mul_unsigned<multiplier>(xs.real), FF::template mul_unsigned<multiplier>(xs.im1),
+      FF::template mul_unsigned<multiplier>(xs.im2), FF::template mul_unsigned<multiplier>(xs.im3)};
+  }
+
+  template <unsigned MODULUS_MULTIPLE = 1>
+  static constexpr HOST_DEVICE_INLINE ExtensionWide sqr_wide(const ExtensionField& xs)
+  {
+    // TODO: change to a more efficient squaring
+    return mul_wide<MODULUS_MULTIPLE>(xs, xs);
+  }
+
+  template <unsigned MODULUS_MULTIPLE = 1>
+  static constexpr HOST_DEVICE_INLINE ExtensionField sqr(const ExtensionField& xs)
+  {
+    // TODO: change to a more efficient squaring
+    return xs * xs;
+  }
+
+  template <unsigned MODULUS_MULTIPLE = 1>
+  static constexpr HOST_DEVICE_INLINE ExtensionField neg(const ExtensionField& xs)
+  {
+    return {FF::neg(xs.real), FF::neg(xs.im1), FF::neg(xs.im2), FF::neg(xs.im3)};
+  }
+
+  // inverse of zero is set to be zero which is what we want most of the time
+  static constexpr HOST_DEVICE_INLINE ExtensionField inverse(const ExtensionField& xs)
+  {
+    FF x, x0, x2;
+    if (CONFIG::nonresidue_is_negative) {
+      x0 = FF::reduce(
+        FF::sqr_wide(xs.real) +
+        FF::template mul_unsigned<CONFIG::nonresidue>(FF::mul_wide(xs.im1, xs.im3 + xs.im3) - FF::sqr_wide(xs.im2)));
+      x2 = FF::reduce(
+        FF::mul_wide(xs.real, xs.im2 + xs.im2) - FF::sqr_wide(xs.im1) +
+        FF::template mul_unsigned<CONFIG::nonresidue>(FF::sqr_wide(xs.im3)));
+      x = FF::reduce(FF::sqr_wide(x0) + FF::template mul_unsigned<CONFIG::nonresidue>(FF::sqr_wide(x2)));
+    } else {
+      x0 = FF::reduce(
+        FF::sqr_wide(xs.real) -
+        FF::template mul_unsigned<CONFIG::nonresidue>(FF::mul_wide(xs.im1, xs.im3 + xs.im3) - FF::sqr_wide(xs.im2)));
+      x2 = FF::reduce(
+        FF::mul_wide(xs.real, xs.im2 + xs.im2) - FF::sqr_wide(xs.im1) -
+        FF::template mul_unsigned<CONFIG::nonresidue>(FF::sqr_wide(xs.im3)));
+      x = FF::reduce(FF::sqr_wide(x0) - FF::template mul_unsigned<CONFIG::nonresidue>(FF::sqr_wide(x2)));
+    }
+    FF x_inv = FF::inverse(x);
+    x0 = x0 * x_inv;
+    x2 = x2 * x_inv;
+    return {
+      FF::reduce(
+        (CONFIG::nonresidue_is_negative
+           ? (FF::mul_wide(xs.real, x0) + FF::template mul_unsigned<CONFIG::nonresidue>(FF::mul_wide(xs.im2, x2)))
+           : (FF::mul_wide(xs.real, x0)) - FF::template mul_unsigned<CONFIG::nonresidue>(FF::mul_wide(xs.im2, x2)))),
+      FF::reduce(
+        (CONFIG::nonresidue_is_negative
+           ? FWide::neg(FF::template mul_unsigned<CONFIG::nonresidue>(FF::mul_wide(xs.im3, x2)))
+           : FF::template mul_unsigned<CONFIG::nonresidue>(FF::mul_wide(xs.im3, x2))) -
+        FF::mul_wide(xs.im1, x0)),
+      FF::reduce(FF::mul_wide(xs.im2, x0) - FF::mul_wide(xs.real, x2)),
+      FF::reduce(FF::mul_wide(xs.im1, x2) - FF::mul_wide(xs.im3, x0)),
+    };
+  }
+};
+
+template <class CONFIG>
+struct SharedMemory<ExtensionField<CONFIG>> {
+  __device__ ExtensionField<CONFIG>* getPointer()
+  {
+    extern __shared__ ExtensionField<CONFIG> s_ext4_scalar_[];
+    return s_ext4_scalar_;
+  }
+};

icicle/include/fields/snark_fields/bls12_377_base.cuh

@@ -1,196 +1,10 @@
 #pragma once
-#ifndef BLS12_377_PARAMS_H
-#define BLS12_377_PARAMS_H
+#ifndef BLS12_377_BASE_PARAMS_H
+#define BLS12_377_BASE_PARAMS_H
 
-#include "utils/storage.cuh"
+#include "fields/storage.cuh"
 
 namespace bls12_377 {
-  struct fp_config {
-    static constexpr unsigned limbs_count = 8;
-    static constexpr unsigned omegas_count = 47;
-    static constexpr unsigned modulus_bit_count = 253;
-    static constexpr unsigned num_of_reductions = 1;
-
-    static constexpr storage<limbs_count> modulus = {0x00000001, 0x0a118000, 0xd0000001, 0x59aa76fe,
-                                                     0x5c37b001, 0x60b44d1e, 0x9a2ca556, 0x12ab655e};
-    static constexpr storage<limbs_count> modulus_2 = {0x00000002, 0x14230000, 0xa0000002, 0xb354edfd,
-                                                       0xb86f6002, 0xc1689a3c, 0x34594aac, 0x2556cabd};
-    static constexpr storage<limbs_count> modulus_4 = {0x00000004, 0x28460000, 0x40000004, 0x66a9dbfb,
-                                                       0x70dec005, 0x82d13479, 0x68b29559, 0x4aad957a};
-    static constexpr storage<limbs_count> neg_modulus = {0xffffffff, 0xf5ee7fff, 0x2ffffffe, 0xa6558901,
-                                                         0xa3c84ffe, 0x9f4bb2e1, 0x65d35aa9, 0xed549aa1};
-    static constexpr storage<2 * limbs_count> modulus_wide = {
-      0x00000001, 0x0a118000, 0xd0000001, 0x59aa76fe, 0x5c37b001, 0x60b44d1e, 0x9a2ca556, 0x12ab655e,
-      0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000};
-    static constexpr storage<2 * limbs_count> modulus_squared = {
-      0x00000001, 0x14230000, 0xe0000002, 0xc7dd4d2f, 0x8585d003, 0x08ee1bd4, 0xe57fc56e, 0x7e7557e3,
-      0x483a709d, 0x1fdebb41, 0x5678f4e6, 0x8ea77334, 0xc19c3ec5, 0xd717de29, 0xe2340781, 0x015c8d01};
-    static constexpr storage<2 * limbs_count> modulus_squared_2 = {
-      0x00000002, 0x28460000, 0xc0000004, 0x8fba9a5f, 0x0b0ba007, 0x11dc37a9, 0xcaff8adc, 0xfceaafc7,
-      0x9074e13a, 0x3fbd7682, 0xacf1e9cc, 0x1d4ee668, 0x83387d8b, 0xae2fbc53, 0xc4680f03, 0x02b91a03};
-    static constexpr storage<2 * limbs_count> modulus_squared_4 = {
-      0x00000004, 0x508c0000, 0x80000008, 0x1f7534bf, 0x1617400f, 0x23b86f52, 0x95ff15b8, 0xf9d55f8f,
-      0x20e9c275, 0x7f7aed05, 0x59e3d398, 0x3a9dccd1, 0x0670fb16, 0x5c5f78a7, 0x88d01e07, 0x05723407};
-
-    static constexpr storage<limbs_count> m = {0x151e79ea, 0xf5204c21, 0x8d69e258, 0xfd0a180b,
-                                               0xfaa80548, 0xe4e51e49, 0xc40b2c9e, 0x36d9491e};
-    static constexpr storage<limbs_count> one = {0x00000001, 0x00000000, 0x00000000, 0x00000000,
-                                                 0x00000000, 0x00000000, 0x00000000, 0x00000000};
-    static constexpr storage<limbs_count> zero = {0x00000000, 0x00000000, 0x00000000, 0x00000000,
-                                                  0x00000000, 0x00000000, 0x00000000, 0x00000000};
-    static constexpr storage<limbs_count> montgomery_r = {0xfffffff3, 0x7d1c7fff, 0x6ffffff2, 0x7257f50f,
-                                                          0x512c0fee, 0x16d81575, 0x2bbb9a9d, 0x0d4bda32};
-    static constexpr storage<limbs_count> montgomery_r_inv = {0x1beeec02, 0x4122dd1a, 0x74fee875, 0xbd1eae95,
-                                                              0x27b28e2f, 0x838557e2, 0x2290c02c, 0x07b30191};
-
-    static constexpr storage_array<omegas_count, limbs_count> omega = {
-      {{0x00000000, 0x0a118000, 0xd0000001, 0x59aa76fe, 0x5c37b001, 0x60b44d1e, 0x9a2ca556, 0x12ab655e},
-       {0x00000001, 0x8f1a4000, 0xb0000001, 0xcf664765, 0x970dec00, 0x23ed1347, 0x00000000, 0x00000000},
-       {0xfbfa0a01, 0x0f830f7e, 0xd75769a0, 0x20f8b46c, 0xf05d5033, 0x7108bd18, 0x0788de01, 0x07405e08},
-       {0x60b9bdae, 0xc78085a6, 0x789094f5, 0x3116ec22, 0xce87d660, 0x0a02a81d, 0xc2a94856, 0x0ead8236},
-       {0x3e83a7cc, 0x6ffc39d9, 0x958a0a74, 0x117d996e, 0x0b92e8c9, 0xc242289d, 0x29d977d6, 0x0484efb4},
-       {0x0111ec3f, 0x15455b00, 0xc5f6be6f, 0x6b62d7af, 0x337f2d07, 0xfcba0365, 0x43fccd26, 0x0f151842},
-       {0xc31ec69b, 0x57951b2e, 0x2a37ce1f, 0x3e0a4be7, 0xcf3b198a, 0x960aeb4a, 0x341fd5cd, 0x04fb0673},
-       {0xa921851f, 0x71c1b78e, 0x7808f239, 0x3c26340c, 0x976fb990, 0xbcc8f69b, 0xe880dc71, 0x06a5edb2},
-       {0xc0f5679e, 0x7619eab5, 0x0dc0b9cd, 0x1f4cd10e, 0xbf6a480a, 0x7e1b70aa, 0x7f5461bb, 0x0ffc66da},
-       {0xec5cbab2, 0x8159806d, 0x498264a3, 0x14ea1333, 0xe3abfaa6, 0x56bbe1d8, 0x02aa031f, 0x09d2b5c4},
-       {0xc010c48a, 0xd2aa9562, 0x3b004b60, 0x447e5c11, 0x11e243bb, 0xd5a21c13, 0x0ab418b1, 0x01eab23e},
-       {0xacff6986, 0x08715ee8, 0xa93924d0, 0xab01878a, 0x6e9ae5c4, 0xbfbc5e71, 0x26b08d6e, 0x0f8000bf},
-       {0x3ddbc679, 0x06bc13b0, 0x615256ce, 0x7269a1f1, 0x1f5221a2, 0xf7716fbf, 0x8c66c14f, 0x0fa1f02c},
-       {0x906f531f, 0xdd40f131, 0x30728eff, 0xb06b29c7, 0x88839294, 0xc891fd19, 0x646978e8, 0x04e88447},
-       {0x6e259cdc, 0xb1e4b769, 0x00514e5e, 0xbcb0b709, 0x05113e7f, 0x74edb7c0, 0xe92e22af, 0x10c88511},
-       {0x240ede5b, 0xebb2e898, 0x42cd84c6, 0xc2639185, 0x9408f956, 0xf79e8391, 0x94e87a7d, 0x06872fa1},
-       {0x260678ff, 0xf8522249, 0xa8de9973, 0x6148cb16, 0x5a4e8d56, 0x5750f3f4, 0xbaeaf0c3, 0x0e805156},
-       {0x3d766f80, 0x1b4b71cf, 0x1069012d, 0x47d21195, 0x9151ebec, 0x5635235f, 0x2b13c808, 0x093f7d91},
-       {0x4637701d, 0x0848f958, 0x4c8353af, 0x8a750076, 0x0ef6174a, 0x485f4e4f, 0xf38db632, 0x078d97a1},
-       {0x66a16869, 0x50c487c1, 0xd1fd4525, 0x380a66ab, 0x265e8539, 0xd455a01a, 0x064b5334, 0x0cd62875},
-       {0x3358eb25, 0xdbc547bc, 0x722037db, 0x8909d398, 0x5e705b6d, 0x8b7075b5, 0x9bdaf407, 0x02694bb2},
-       {0xf45b9621, 0x102fbfb0, 0xf04faac0, 0xe80f4241, 0x7ca61177, 0x0b830bfd, 0x7033169d, 0x10521892},
-       {0xcc943028, 0xed2576ad, 0xfa4c6090, 0x846e49bc, 0x0049d8e6, 0xc74c1865, 0x665d7be5, 0x0e9c5a12},
-       {0xafeb494b, 0x97319dcd, 0x1d78404c, 0xab30c83e, 0xf26ffe90, 0x452d8a48, 0xa36452c7, 0x0bfc2e92},
-       {0xedc626c3, 0xf30e312d, 0xcf1f3a94, 0x8367a7ca, 0x917a1b28, 0x621e15e1, 0xf2e93b82, 0x07cd59f8},
-       {0xf02ba42c, 0x553085d9, 0x1119b10d, 0x59662159, 0x6b8ea03f, 0xaa670958, 0x7ce92983, 0x066f6f5f},
-       {0x4dd87a5e, 0xf423a283, 0xd9a4c364, 0x1fe46601, 0xbfdc7e9b, 0xda4addbf, 0x3bf94b2b, 0x0a7f2bd8},
-       {0xe5f8848a, 0x270a2326, 0xa727567d, 0x97d14afa, 0x48746fc7, 0x1a3a5a4e, 0xa42f077a, 0x0044e4b1},
-       {0x20b7298a, 0xd7652451, 0x65013b06, 0xc7c9a0b7, 0xad0d8457, 0x479b82a9, 0x0c99f5ce, 0x0bef1e5a},
-       {0x1912f7fa, 0x77d7da1d, 0x299fd7d6, 0xbcb7a5b2, 0x142a4480, 0x705e45dd, 0xb492dbd8, 0x0dc835fd},
-       {0xa0234d2d, 0xe943054c, 0xe5f5be5e, 0x673b0ee0, 0x5048a19a, 0xcdd48e41, 0xabc3cb99, 0x0997d277},
-       {0xa9966ac4, 0x1ae0ea67, 0xda83fb3b, 0x4e2dbb1c, 0x0b51380e, 0xf77cf749, 0xb28a7670, 0x048b4b0e},
-       {0xb14361d4, 0x7f1db43f, 0x25ab6d51, 0x7927e578, 0x383bf21e, 0xb43e52a5, 0xd27fa99f, 0x077595e9},
-       {0xa90a2740, 0xfe3ca4f0, 0x512a7c7a, 0xd259ff36, 0xb41fe696, 0xbca3176a, 0xf33132ce, 0x05bd5ea3},
-       {0xf284f768, 0xdeee484b, 0xe26a0475, 0x2a02e015, 0x88d968c2, 0xf0eb4925, 0x82a391c9, 0x0620ce9e},
-       {0xbd83a3da, 0xd3b69b29, 0xe02ce197, 0x9543950f, 0xc2f87783, 0x80799665, 0xc15be215, 0x11ce8199},
-       {0x1b29736e, 0x8f267f19, 0x1d5a0c3a, 0xa2e04d58, 0x1ae99514, 0x76803064, 0x57f7c806, 0x12129439},
-       {0xf32d6bac, 0xa0b973d4, 0xf0d81b72, 0xae951889, 0x2e2daa0a, 0x51dbe098, 0x40d9af8f, 0x04679474},
-       {0x22df9f13, 0x56313de8, 0x599e7536, 0xe2e75200, 0x6d163e50, 0xa1b4fce7, 0xc8111763, 0x0aec2172},
-       {0x355dd694, 0x4258374d, 0x44c76a20, 0x5c31e8ac, 0xaa5fd062, 0x9b473969, 0x1a37b6b4, 0x0a693d77},
-       {0x44ddbbdc, 0xbafb92a6, 0x26b01974, 0x63c7a02d, 0x5f28a274, 0x0ff86e13, 0x867f2e29, 0x0a7b462a},
-       {0xd5fba57b, 0x90684fea, 0xe0defe98, 0xed237883, 0x030ae924, 0xc502b692, 0xe7a1ec2c, 0x08aa58e8},
-       {0x5e9020dd, 0xade9d4b4, 0x87db8813, 0x489259d2, 0x25051238, 0x5ddce740, 0xb5bc4d11, 0x0c775db1},
-       {0x293f8481, 0xd52cc17a, 0x6f133205, 0x041178fb, 0xb2961832, 0xbbc70d18, 0x481760cd, 0x073d34d1},
-       {0xfdacff58, 0x8215b91d, 0x98331645, 0xd8d9177d, 0x439e803c, 0xe85223ad, 0xcca42c1f, 0x04aa8ef0},
-       {0x01ab3a4d, 0x006f60fa, 0x814ba450, 0xe6600e15, 0xdf9eb147, 0xbde4df36, 0x33760d7b, 0x055d58fa},
-       {0xec2a895e, 0x476ef4a4, 0x63e3f04a, 0x9b506ee3, 0xd1a8a12f, 0x60c69477, 0x0cb92cc1, 0x11d4b7f6}}};
-
-    static constexpr storage_array<omegas_count, limbs_count> omega_inv = {
-      {{0x00000000, 0x0a118000, 0xd0000001, 0x59aa76fe, 0x5c37b001, 0x60b44d1e, 0x9a2ca556, 0x12ab655e},
-       {0x00000000, 0x7af74000, 0x1fffffff, 0x8a442f99, 0xc529c400, 0x3cc739d6, 0x9a2ca556, 0x12ab655e},
-       {0xd60fb046, 0xc9fa190c, 0xc5b4674e, 0xdb5c179b, 0xbc7b8726, 0x2b2bce0b, 0xbf6e69bf, 0x0e4eb338},
-       {0x8ffc4ed5, 0x74732d1f, 0xb7f2eefc, 0x42d9f590, 0xa24dd4dd, 0xf70461e5, 0xef64676f, 0x03b6eba4},
-       {0x102bbab0, 0x5a21f98a, 0x8d8e2efb, 0xa6a147a9, 0x7612906f, 0x0eb4f005, 0x47d8d2e3, 0x0e1a5481},
-       {0xd01e5aa8, 0x6e509add, 0x6e3f123d, 0xe1582468, 0x8274db24, 0xbd6313ee, 0xd173a634, 0x05d5836e},
-       {0xe975c0cf, 0x6aab3344, 0x6f1dc38e, 0xca362e0e, 0x1dd1743a, 0x2fe72cda, 0xc1b4c4c2, 0x0c1c956e},
-       {0xec89a64f, 0x59fe97a0, 0xe8de5d4c, 0x579617d7, 0xc9c1ea7b, 0x256a305b, 0x53fa131b, 0x01ffae4e},
-       {0x29bcb088, 0x463a73ff, 0xe1438e80, 0xee9e9a5e, 0x3c9369e4, 0x2a00951f, 0x80a32052, 0x09711183},
-       {0x4bec8dd2, 0xa36899db, 0x96393687, 0x2946872e, 0x842df3c8, 0xd4b5734f, 0x5f5cd8fb, 0x0834098f},
-       {0xe3c711b9, 0x4bc485f6, 0x648d1d7e, 0xf43a2598, 0xee88abaa, 0x7f981a0e, 0xec6a3f27, 0x0c88c9c3},
-       {0x49046b52, 0x42bcc6c2, 0x56ab9ecc, 0xcc77294a, 0xe4df3ddd, 0x02ecb41a, 0x67f76726, 0x0e567d22},
-       {0x91c64fc2, 0x1cc56cc3, 0xd16a490b, 0x8cb71e65, 0x14fac366, 0x984be37e, 0xa25d7ba5, 0x0a08e032},
-       {0xd4f5941e, 0x966d9739, 0xe5772a73, 0x5805deb6, 0x5c1f970c, 0xe4eb0d33, 0xbdf35409, 0x039715db},
-       {0xcc6518ac, 0x8419686c, 0x9c7a2366, 0x96dec3a8, 0x71724384, 0xefbfcac6, 0xaf34c239, 0x0c44b99a},
-       {0xc18ff4fd, 0xcb66fe1b, 0x86c8d586, 0x588e18b3, 0x1dfab57c, 0xc6e6d2a3, 0x7d7d4efd, 0x10918ad2},
-       {0x97a18f58, 0x56d6cf22, 0xd0d7abd9, 0x11710758, 0x5eb7a9c5, 0xd1a6608b, 0xc4937e38, 0x04059bdb},
-       {0x4b1b63a9, 0x12998cbc, 0xcf420c9f, 0x0f780c6c, 0x129289ad, 0xa5e48723, 0x240a141d, 0x0a3a1223},
-       {0x00db2b48, 0xa43c0e02, 0x933d10ee, 0x76585489, 0xc0ba6a80, 0x12d64af1, 0x2fad8d8e, 0x01940f43},
-       {0x1d75bec9, 0xe29ef6c0, 0xd4b0183b, 0xead287a2, 0xedfd3795, 0x75a017cf, 0x64427c8e, 0x107f8d0f},
-       {0xa26c8c12, 0xa6f4e1d1, 0xf6610f7e, 0x13571553, 0x56701caf, 0xd95e5df6, 0x2263d69d, 0x050e7b89},
-       {0xc161761f, 0x271d7caf, 0xc369a371, 0xf1001d6f, 0x00e60f51, 0x65286415, 0xb74d14b8, 0x00b918f9},
-       {0x03ad3139, 0x01d3f431, 0xa137ce16, 0xe56f6002, 0x1deb42e8, 0x97f53369, 0xaa37cddd, 0x033fa9ac},
-       {0x60cf1330, 0x840f913b, 0x1df5ed87, 0x5610cde6, 0x72b36ddf, 0x858381b0, 0x6f64e0b7, 0x109bf66c},
-       {0x930cee0b, 0x432d3626, 0xf26e8ba3, 0x55ed3efb, 0x14c5457f, 0x802eebcc, 0xe2310f22, 0x00d300e3},
-       {0x4b9ac952, 0x3d29f5ba, 0xc8ea8f94, 0x7c7f2662, 0xcefc3052, 0x736ccb63, 0x0981f3cb, 0x04bfce2f},
-       {0x5d4e643c, 0x3da791ea, 0x85bff013, 0xb6a956ef, 0xd73de6a3, 0x86c629a8, 0x6b8c48a9, 0x0a5a5f55},
-       {0x49c6284a, 0x9ba6aa00, 0xeacbdc63, 0x0b8429fb, 0xedafdf37, 0x9b9c6c5b, 0xad0c78c6, 0x009907e8},
-       {0x3e47b53f, 0x50380ce2, 0x3a9613fc, 0x6ea3c2d3, 0x4c87ab50, 0xfe743105, 0xd192221c, 0x07871979},
-       {0xe978594b, 0x4ddd3320, 0x3abe3f79, 0xe5f36fbe, 0xe4dcff8e, 0x5dba9ef2, 0x7105148f, 0x0bfc27e2},
-       {0x498fb549, 0xd5993cd5, 0x09da9272, 0x718adcee, 0x72bd5bc0, 0x9e03cbb4, 0xc592813f, 0x07206942},
-       {0x78fd3239, 0xaf29730b, 0x40c3e723, 0xbd907ac9, 0x77f214f7, 0x5dcc0aad, 0xb05fb3a1, 0x02d958da},
-       {0xdf80223d, 0x55f432c9, 0x11a2fed9, 0x23daf2f6, 0x41ae8c34, 0x9e43e003, 0x95f22373, 0x0d51533b},
-       {0x7998b62c, 0xbb53132b, 0x22c9b4aa, 0x064a9186, 0x71d61334, 0xd56de253, 0x04e416f6, 0x10fcf25f},
-       {0xdddb58ec, 0x41f8042f, 0x10886d85, 0x7dd54384, 0x622ff4b4, 0x19544f90, 0x050cc539, 0x02f0b49a},
-       {0xa39b02a3, 0x8a3de898, 0xdc94422c, 0x068b2992, 0xf493db31, 0x1c5f019a, 0x11b0f668, 0x066b1790},
-       {0x78500f1a, 0x98310dd7, 0x735ccb27, 0x1c6050bf, 0xb2081df4, 0x07b6fa7f, 0xfa0f1e20, 0x003edf24},
-       {0x89b0ca6f, 0xb4d938e2, 0x2c897570, 0x0214eb59, 0x2d4cf27a, 0x56c45327, 0x3ed546a4, 0x10a2f358},
-       {0xef01ed78, 0xf2828212, 0xf103c9ca, 0xa66094ac, 0x7a2d5573, 0xdceb481d, 0x8af46aab, 0x0190fcde},
-       {0x526bf9fc, 0x023031cc, 0x79c209ba, 0x0e4136c0, 0x3ec42e5c, 0xe5234df1, 0x1d455234, 0x00cb9592},
-       {0x33bf2a1c, 0x842b0c9c, 0xa29b9236, 0x1fd43c95, 0xc06795d3, 0x6b37a603, 0x0c1b712a, 0x00017b17},
-       {0xaf858193, 0x2b955be2, 0x5fb5e378, 0xa513d8be, 0xa326aeb9, 0x88c4ebeb, 0xf3d45990, 0x00c378e2},
-       {0x6464580f, 0x33e6c8c0, 0x3c4aa09f, 0x9d560eb3, 0xcc98f404, 0xb3f1a899, 0x8ca24b48, 0x012c1ea5},
-       {0xe3b4dc56, 0xa0594a67, 0x91b698e1, 0xc8e6b582, 0x8df78057, 0x711cadbf, 0x396466f8, 0x0049abdf},
-       {0x4ffa086a, 0xecc89610, 0xca06afc6, 0x4db82291, 0x8f3a6426, 0x9ae7c68c, 0x2a874432, 0x0b3dae8c},
-       {0x3b3625b6, 0x1e62401f, 0x28471e5a, 0xd0692164, 0x5cad6b77, 0xb85aa9ec, 0xaa95acf2, 0x063e4b66},
-       {0xb9112c51, 0x2542c2b2, 0x6e23b3ce, 0x36ead8da, 0x76476754, 0x9a268d13, 0xa1ad7cf1, 0x121f44ad}}};
-
-    static constexpr storage_array<omegas_count, limbs_count> inv = {
-      {{0x00000001, 0x8508c000, 0x68000000, 0xacd53b7f, 0x2e1bd800, 0x305a268f, 0x4d1652ab, 0x0955b2af},
-       {0x00000001, 0xc78d2000, 0x1c000000, 0x033fd93f, 0xc529c401, 0xc88739d6, 0xf3a17c00, 0x0e008c06},
-       {0x00000001, 0xe8cf5000, 0xf6000000, 0x2e75281e, 0x90b0ba01, 0x949dc37a, 0xc6e710ab, 0x1055f8b2},
-       {0x00000001, 0xf9706800, 0xe3000000, 0x440fcf8e, 0x76743501, 0xfaa9084c, 0xb089db00, 0x1180af08},
-       {0x00000001, 0x01c0f400, 0xd9800001, 0x4edd2346, 0x6955f281, 0xadaeaab5, 0xa55b402b, 0x12160a33},
-       {0x00000001, 0x05e93a00, 0xd4c00001, 0x5443cd22, 0xe2c6d141, 0x07317be9, 0x1fc3f2c1, 0x1260b7c9},
-       {0x00000001, 0x07fd5d00, 0xd2600001, 0x56f72210, 0x1f7f40a1, 0xb3f2e484, 0xdcf84c0b, 0x12860e93},
-       {0x00000001, 0x09076e80, 0xd1300001, 0x5850cc87, 0x3ddb7851, 0x0a5398d1, 0x3b9278b1, 0x1298b9f9},
-       {0x00000001, 0x098c7740, 0x50980001, 0x58fda1c3, 0xcd099429, 0xb583f2f7, 0xeadf8f03, 0x12a20fab},
-       {0x00000001, 0x09cefba0, 0x104c0001, 0x59540c61, 0x14a0a215, 0x0b1c200b, 0x42861a2d, 0x12a6ba85},
-       {0x00000001, 0x09f03dd0, 0xf0260001, 0x597f41af, 0xb86c290b, 0xb5e83694, 0xee595fc1, 0x12a90ff1},
-       {0x00000001, 0x0a00dee8, 0x60130001, 0x5994dc57, 0x8a51ec86, 0x0b4e41d9, 0x4443028c, 0x12aa3aa8},
-       {0x00000001, 0x0a092f74, 0x18098001, 0xd99fa9ab, 0xf344ce43, 0x3601477b, 0x6f37d3f1, 0x12aad003},
-       {0x00000001, 0x0a0d57ba, 0xf404c001, 0x99a51054, 0x27be3f22, 0xcb5aca4d, 0x04b23ca3, 0x12ab1ab1},
-       {0x00000001, 0x0a0f6bdd, 0xe2026001, 0xf9a7c3a9, 0xc1faf791, 0x16078bb5, 0xcf6f70fd, 0x12ab4007},
-       {0x80000001, 0x0a1075ee, 0x59013001, 0xa9a91d54, 0x0f1953c9, 0xbb5dec6a, 0x34ce0b29, 0x12ab52b3},
-       {0x40000001, 0x0a10faf7, 0x94809801, 0x81a9ca29, 0x35a881e5, 0x0e091cc4, 0xe77d5840, 0x12ab5c08},
-       {0xa0000001, 0x0a113d7b, 0x32404c01, 0x6daa2094, 0x48f018f3, 0x375eb4f1, 0xc0d4fecb, 0x12ab60b3},
-       {0xd0000001, 0x0a115ebd, 0x81202601, 0x63aa4bc9, 0xd293e47a, 0xcc098107, 0x2d80d210, 0x12ab6309},
-       {0xe8000001, 0x0a116f5e, 0x28901301, 0xdeaa6164, 0x1765ca3d, 0x965ee713, 0xe3d6bbb3, 0x12ab6433},
-       {0x74000001, 0x0a1177af, 0x7c480981, 0x9c2a6c31, 0xb9cebd1f, 0xfb899a18, 0x3f01b084, 0x12ab64c9},
-       {0xba000001, 0x0a117bd7, 0x262404c1, 0x7aea7198, 0x8b033690, 0xae1ef39b, 0xec972aed, 0x12ab6513},
-       {0xdd000001, 0x0a117deb, 0x7b120261, 0xea4a744b, 0xf39d7348, 0x0769a05c, 0x4361e822, 0x12ab6539},
-       {0xee800001, 0x0a117ef5, 0x25890131, 0x21fa75a5, 0xa7ea91a5, 0x340ef6bd, 0xeec746bc, 0x12ab654b},
-       {0xf7400001, 0x0a117f7a, 0xfac48099, 0x3dd27651, 0x021120d3, 0x4a61a1ee, 0x4479f609, 0x12ab6555},
-       {0x7ba00001, 0x0a117fbd, 0x6562404d, 0x4bbe76a8, 0x2f24686a, 0xd58af786, 0xef534daf, 0x12ab6559},
-       {0xbdd00001, 0x0a117fde, 0x9ab12027, 0xd2b476d3, 0x45ae0c35, 0x1b1fa252, 0x44bff983, 0x12ab655c},
-       {0x5ee80001, 0x0a117fef, 0x35589014, 0x962f76e9, 0x50f2de1b, 0xbde9f7b8, 0x6f764f6c, 0x12ab655d},
-       {0xaf740001, 0x8a117ff7, 0x02ac480a, 0x77ecf6f4, 0x5695470e, 0x8f4f226b, 0x04d17a61, 0x12ab655e},
-       {0xd7ba0001, 0xca117ffb, 0x69562405, 0xe8cbb6f9, 0xd9667b87, 0xf801b7c4, 0x4f7f0fdb, 0x12ab655e},
-       {0xebdd0001, 0x6a117ffd, 0x1cab1203, 0xa13b16fc, 0x9acf15c4, 0x2c5b0271, 0x74d5da99, 0x12ab655e},
-       {0xf5ee8001, 0x3a117ffe, 0x76558902, 0xfd72c6fd, 0xfb8362e2, 0xc687a7c7, 0x87813ff7, 0x12ab655e},
-       {0x7af74001, 0xa2117fff, 0x232ac481, 0x2b8e9efe, 0x2bdd8972, 0x139dfa73, 0x90d6f2a7, 0x12ab655e},
-       {0xbd7ba001, 0x56117fff, 0x79956241, 0xc29c8afe, 0xc40a9cb9, 0xba2923c8, 0x9581cbfe, 0x12ab655e},
-       {0xdebdd001, 0x30117fff, 0xa4cab121, 0x8e2380fe, 0x9021265d, 0x8d6eb873, 0x97d738aa, 0x12ab655e},
-       {0xef5ee801, 0x1d117fff, 0xba655891, 0x73e6fbfe, 0xf62c6b2f, 0x771182c8, 0x9901ef00, 0x12ab655e},
-       {0xf7af7401, 0x13917fff, 0xc532ac49, 0x66c8b97e, 0xa9320d98, 0x6be2e7f3, 0x99974a2b, 0x12ab655e},
-       {0xfbd7ba01, 0x0ed17fff, 0xca995625, 0xe039983e, 0x02b4decc, 0xe64b9a89, 0x99e1f7c0, 0x12ab655e},
-       {0xfdebdd01, 0x0c717fff, 0xcd4cab13, 0x1cf2079e, 0xaf764767, 0xa37ff3d3, 0x9a074e8b, 0x12ab655e},
-       {0xfef5ee81, 0x0b417fff, 0xcea6558a, 0x3b4e3f4e, 0x05d6fbb4, 0x021a2079, 0x9a19f9f1, 0x12ab655e},
-       {0xff7af741, 0x8aa97fff, 0xcf532ac5, 0xca7c5b26, 0xb10755da, 0xb16736cb, 0x9a234fa3, 0x12ab655e},
-       {0xffbd7ba1, 0x4a5d7fff, 0xcfa99563, 0x12136912, 0x069f82ee, 0x090dc1f5, 0x9a27fa7d, 0x12ab655e},
-       {0xffdebdd1, 0x2a377fff, 0xcfd4cab2, 0xb5def008, 0xb16b9977, 0xb4e10789, 0x9a2a4fe9, 0x12ab655e},
-       {0xffef5ee9, 0x9a247fff, 0xcfea6559, 0x87c4b383, 0x06d1a4bc, 0x0acaaa54, 0x9a2b7aa0, 0x12ab655e},
-       {0xfff7af75, 0x521affff, 0x4ff532ad, 0xf0b79541, 0x3184aa5e, 0x35bf7bb9, 0x9a2c0ffb, 0x12ab655e},
-       {0xfffbd7bb, 0x2e163fff, 0x0ffa9957, 0x25310620, 0xc6de2d30, 0xcb39e46b, 0x9a2c5aa8, 0x12ab655e},
-       {0xfffdebde, 0x1c13dfff, 0x6ffd4cac, 0xbf6dbe8f, 0x118aee98, 0x95f718c5, 0x9a2c7fff, 0x12ab655e}}};
-  };
-
   struct fq_config {
     static constexpr unsigned limbs_count = 12;
     static constexpr unsigned omegas_count = 48;
@@ -521,41 +335,11 @@ namespace bls12_377 {
        {0xfffdebde, 0x0ff7ffff, 0x0fffa3d3, 0x8e4c751f, 0x6bcccc32, 0xb7275e5b, 0xdc08ab03, 0x0321276d, 0x28f6304f,
         0xdd22a6ac, 0x17c50a31, 0x01ae3a46}}};
 
-    // i^2, the square of the imaginary unit for the extension field
-    static constexpr uint32_t i_squared = 5;
-    // true if i^2 is negative
-    static constexpr bool i_squared_is_negative = true;
+    // nonresidue to generate the extension field
+    static constexpr uint32_t nonresidue = 5;
+    // true if nonresidue is negative
+    static constexpr bool nonresidue_is_negative = true;
   };
-
-  // G1 and G2 generators
-  static constexpr storage<fq_config::limbs_count> g1_gen_x = {0xb21be9ef, 0xeab9b16e, 0xffcd394e, 0xd5481512,
-                                                               0xbd37cb5c, 0x188282c8, 0xaa9d41bb, 0x85951e2c,
-                                                               0xbf87ff54, 0xc8fc6225, 0xfe740a67, 0x008848de};
-  static constexpr storage<fq_config::limbs_count> g1_gen_y = {0x559c8ea6, 0xfd82de55, 0x34a9591a, 0xc2fe3d36,
-                                                               0x4fb82305, 0x6d182ad4, 0xca3e52d9, 0xbd7fb348,
-                                                               0x30afeec4, 0x1f674f5d, 0xc5102eff, 0x01914a69};
-  static constexpr storage<fq_config::limbs_count> g2_gen_x_re = {0x7c005196, 0x74e3e48f, 0xbb535402, 0x71889f52,
-                                                                  0x57db6b9b, 0x7ea501f5, 0x203e5031, 0xc565f071,
-                                                                  0xa3841d01, 0xc89630a2, 0x71c785fe, 0x018480be};
-  static constexpr storage<fq_config::limbs_count> g2_gen_x_im = {0x6ea16afe, 0xb26bfefa, 0xbff76fe6, 0x5cf89984,
-                                                                  0x0799c9de, 0xe7223ece, 0x6651cecb, 0x532777ee,
-                                                                  0xb1b140d5, 0x70dc5a51, 0xe7004031, 0x00ea6040};
-  static constexpr storage<fq_config::limbs_count> g2_gen_y_re = {0x09fd4ddf, 0xf0940944, 0x6d8c7c2e, 0xf2cf8888,
-                                                                  0xf832d204, 0xe458c282, 0x74b49a58, 0xde03ed72,
-                                                                  0xcbb2efb4, 0xd960736b, 0x5d446f7b, 0x00690d66};
-  static constexpr storage<fq_config::limbs_count> g2_gen_y_im = {0x85eb8f93, 0xd9a1cdd1, 0x5e52270b, 0x4279b83f,
-                                                                  0xcee304c2, 0x2463b01a, 0x3d591bf1, 0x61ef11ac,
-                                                                  0x151a70aa, 0x9e549da3, 0xd2835518, 0x00f8169f};
-
-  static constexpr storage<fq_config::limbs_count> weierstrass_b = {0x00000001, 0x00000000, 0x00000000, 0x00000000,
-                                                                    0x00000000, 0x00000000, 0x00000000, 0x00000000,
-                                                                    0x00000000, 0x00000000, 0x00000000, 0x00000000};
-  static constexpr storage<fq_config::limbs_count> weierstrass_b_g2_re = {
-    0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000,
-    0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000};
-  static constexpr storage<fq_config::limbs_count> weierstrass_b_g2_im = {
-    0x9999999a, 0x1c9ed999, 0x1ccccccd, 0x0dd39e5c, 0x3c6bf800, 0x129207b6,
-    0xcd5fd889, 0xdc7b4f91, 0x7460c589, 0x43bd0373, 0xdb0fd6f3, 0x010222f6};
 } // namespace bls12_377
 
-#endif
+#endif

icicle/include/fields/snark_fields/bls12_377_scalar.cuh

@@ -0,0 +1,195 @@
+#pragma once
+#ifndef BLS12_377_SCALAR_PARAMS_H
+#define BLS12_377_SCALAR_PARAMS_H
+
+#include "fields/storage.cuh"
+
+namespace bls12_377 {
+  struct fp_config {
+    static constexpr unsigned limbs_count = 8;
+    static constexpr unsigned omegas_count = 47;
+    static constexpr unsigned modulus_bit_count = 253;
+    static constexpr unsigned num_of_reductions = 1;
+
+    static constexpr storage<limbs_count> modulus = {0x00000001, 0x0a118000, 0xd0000001, 0x59aa76fe,
+                                                     0x5c37b001, 0x60b44d1e, 0x9a2ca556, 0x12ab655e};
+    static constexpr storage<limbs_count> modulus_2 = {0x00000002, 0x14230000, 0xa0000002, 0xb354edfd,
+                                                       0xb86f6002, 0xc1689a3c, 0x34594aac, 0x2556cabd};
+    static constexpr storage<limbs_count> modulus_4 = {0x00000004, 0x28460000, 0x40000004, 0x66a9dbfb,
+                                                       0x70dec005, 0x82d13479, 0x68b29559, 0x4aad957a};
+    static constexpr storage<limbs_count> neg_modulus = {0xffffffff, 0xf5ee7fff, 0x2ffffffe, 0xa6558901,
+                                                         0xa3c84ffe, 0x9f4bb2e1, 0x65d35aa9, 0xed549aa1};
+    static constexpr storage<2 * limbs_count> modulus_wide = {
+      0x00000001, 0x0a118000, 0xd0000001, 0x59aa76fe, 0x5c37b001, 0x60b44d1e, 0x9a2ca556, 0x12ab655e,
+      0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000};
+    static constexpr storage<2 * limbs_count> modulus_squared = {
+      0x00000001, 0x14230000, 0xe0000002, 0xc7dd4d2f, 0x8585d003, 0x08ee1bd4, 0xe57fc56e, 0x7e7557e3,
+      0x483a709d, 0x1fdebb41, 0x5678f4e6, 0x8ea77334, 0xc19c3ec5, 0xd717de29, 0xe2340781, 0x015c8d01};
+    static constexpr storage<2 * limbs_count> modulus_squared_2 = {
+      0x00000002, 0x28460000, 0xc0000004, 0x8fba9a5f, 0x0b0ba007, 0x11dc37a9, 0xcaff8adc, 0xfceaafc7,
+      0x9074e13a, 0x3fbd7682, 0xacf1e9cc, 0x1d4ee668, 0x83387d8b, 0xae2fbc53, 0xc4680f03, 0x02b91a03};
+    static constexpr storage<2 * limbs_count> modulus_squared_4 = {
+      0x00000004, 0x508c0000, 0x80000008, 0x1f7534bf, 0x1617400f, 0x23b86f52, 0x95ff15b8, 0xf9d55f8f,
+      0x20e9c275, 0x7f7aed05, 0x59e3d398, 0x3a9dccd1, 0x0670fb16, 0x5c5f78a7, 0x88d01e07, 0x05723407};
+
+    static constexpr storage<limbs_count> m = {0x151e79ea, 0xf5204c21, 0x8d69e258, 0xfd0a180b,
+                                               0xfaa80548, 0xe4e51e49, 0xc40b2c9e, 0x36d9491e};
+    static constexpr storage<limbs_count> one = {0x00000001, 0x00000000, 0x00000000, 0x00000000,
+                                                 0x00000000, 0x00000000, 0x00000000, 0x00000000};
+    static constexpr storage<limbs_count> zero = {0x00000000, 0x00000000, 0x00000000, 0x00000000,
+                                                  0x00000000, 0x00000000, 0x00000000, 0x00000000};
+    static constexpr storage<limbs_count> montgomery_r = {0xfffffff3, 0x7d1c7fff, 0x6ffffff2, 0x7257f50f,
+                                                          0x512c0fee, 0x16d81575, 0x2bbb9a9d, 0x0d4bda32};
+    static constexpr storage<limbs_count> montgomery_r_inv = {0x1beeec02, 0x4122dd1a, 0x74fee875, 0xbd1eae95,
+                                                              0x27b28e2f, 0x838557e2, 0x2290c02c, 0x07b30191};
+
+    static constexpr storage_array<omegas_count, limbs_count> omega = {
+      {{0x00000000, 0x0a118000, 0xd0000001, 0x59aa76fe, 0x5c37b001, 0x60b44d1e, 0x9a2ca556, 0x12ab655e},
+       {0x00000001, 0x8f1a4000, 0xb0000001, 0xcf664765, 0x970dec00, 0x23ed1347, 0x00000000, 0x00000000},
+       {0xfbfa0a01, 0x0f830f7e, 0xd75769a0, 0x20f8b46c, 0xf05d5033, 0x7108bd18, 0x0788de01, 0x07405e08},
+       {0x60b9bdae, 0xc78085a6, 0x789094f5, 0x3116ec22, 0xce87d660, 0x0a02a81d, 0xc2a94856, 0x0ead8236},
+       {0x3e83a7cc, 0x6ffc39d9, 0x958a0a74, 0x117d996e, 0x0b92e8c9, 0xc242289d, 0x29d977d6, 0x0484efb4},
+       {0x0111ec3f, 0x15455b00, 0xc5f6be6f, 0x6b62d7af, 0x337f2d07, 0xfcba0365, 0x43fccd26, 0x0f151842},
+       {0xc31ec69b, 0x57951b2e, 0x2a37ce1f, 0x3e0a4be7, 0xcf3b198a, 0x960aeb4a, 0x341fd5cd, 0x04fb0673},
+       {0xa921851f, 0x71c1b78e, 0x7808f239, 0x3c26340c, 0x976fb990, 0xbcc8f69b, 0xe880dc71, 0x06a5edb2},
+       {0xc0f5679e, 0x7619eab5, 0x0dc0b9cd, 0x1f4cd10e, 0xbf6a480a, 0x7e1b70aa, 0x7f5461bb, 0x0ffc66da},
+       {0xec5cbab2, 0x8159806d, 0x498264a3, 0x14ea1333, 0xe3abfaa6, 0x56bbe1d8, 0x02aa031f, 0x09d2b5c4},
+       {0xc010c48a, 0xd2aa9562, 0x3b004b60, 0x447e5c11, 0x11e243bb, 0xd5a21c13, 0x0ab418b1, 0x01eab23e},
+       {0xacff6986, 0x08715ee8, 0xa93924d0, 0xab01878a, 0x6e9ae5c4, 0xbfbc5e71, 0x26b08d6e, 0x0f8000bf},
+       {0x3ddbc679, 0x06bc13b0, 0x615256ce, 0x7269a1f1, 0x1f5221a2, 0xf7716fbf, 0x8c66c14f, 0x0fa1f02c},
+       {0x906f531f, 0xdd40f131, 0x30728eff, 0xb06b29c7, 0x88839294, 0xc891fd19, 0x646978e8, 0x04e88447},
+       {0x6e259cdc, 0xb1e4b769, 0x00514e5e, 0xbcb0b709, 0x05113e7f, 0x74edb7c0, 0xe92e22af, 0x10c88511},
+       {0x240ede5b, 0xebb2e898, 0x42cd84c6, 0xc2639185, 0x9408f956, 0xf79e8391, 0x94e87a7d, 0x06872fa1},
+       {0x260678ff, 0xf8522249, 0xa8de9973, 0x6148cb16, 0x5a4e8d56, 0x5750f3f4, 0xbaeaf0c3, 0x0e805156},
+       {0x3d766f80, 0x1b4b71cf, 0x1069012d, 0x47d21195, 0x9151ebec, 0x5635235f, 0x2b13c808, 0x093f7d91},
+       {0x4637701d, 0x0848f958, 0x4c8353af, 0x8a750076, 0x0ef6174a, 0x485f4e4f, 0xf38db632, 0x078d97a1},
+       {0x66a16869, 0x50c487c1, 0xd1fd4525, 0x380a66ab, 0x265e8539, 0xd455a01a, 0x064b5334, 0x0cd62875},
+       {0x3358eb25, 0xdbc547bc, 0x722037db, 0x8909d398, 0x5e705b6d, 0x8b7075b5, 0x9bdaf407, 0x02694bb2},
+       {0xf45b9621, 0x102fbfb0, 0xf04faac0, 0xe80f4241, 0x7ca61177, 0x0b830bfd, 0x7033169d, 0x10521892},
+       {0xcc943028, 0xed2576ad, 0xfa4c6090, 0x846e49bc, 0x0049d8e6, 0xc74c1865, 0x665d7be5, 0x0e9c5a12},
+       {0xafeb494b, 0x97319dcd, 0x1d78404c, 0xab30c83e, 0xf26ffe90, 0x452d8a48, 0xa36452c7, 0x0bfc2e92},
+       {0xedc626c3, 0xf30e312d, 0xcf1f3a94, 0x8367a7ca, 0x917a1b28, 0x621e15e1, 0xf2e93b82, 0x07cd59f8},
+       {0xf02ba42c, 0x553085d9, 0x1119b10d, 0x59662159, 0x6b8ea03f, 0xaa670958, 0x7ce92983, 0x066f6f5f},
+       {0x4dd87a5e, 0xf423a283, 0xd9a4c364, 0x1fe46601, 0xbfdc7e9b, 0xda4addbf, 0x3bf94b2b, 0x0a7f2bd8},
+       {0xe5f8848a, 0x270a2326, 0xa727567d, 0x97d14afa, 0x48746fc7, 0x1a3a5a4e, 0xa42f077a, 0x0044e4b1},
+       {0x20b7298a, 0xd7652451, 0x65013b06, 0xc7c9a0b7, 0xad0d8457, 0x479b82a9, 0x0c99f5ce, 0x0bef1e5a},
+       {0x1912f7fa, 0x77d7da1d, 0x299fd7d6, 0xbcb7a5b2, 0x142a4480, 0x705e45dd, 0xb492dbd8, 0x0dc835fd},
+       {0xa0234d2d, 0xe943054c, 0xe5f5be5e, 0x673b0ee0, 0x5048a19a, 0xcdd48e41, 0xabc3cb99, 0x0997d277},
+       {0xa9966ac4, 0x1ae0ea67, 0xda83fb3b, 0x4e2dbb1c, 0x0b51380e, 0xf77cf749, 0xb28a7670, 0x048b4b0e},
+       {0xb14361d4, 0x7f1db43f, 0x25ab6d51, 0x7927e578, 0x383bf21e, 0xb43e52a5, 0xd27fa99f, 0x077595e9},
+       {0xa90a2740, 0xfe3ca4f0, 0x512a7c7a, 0xd259ff36, 0xb41fe696, 0xbca3176a, 0xf33132ce, 0x05bd5ea3},
+       {0xf284f768, 0xdeee484b, 0xe26a0475, 0x2a02e015, 0x88d968c2, 0xf0eb4925, 0x82a391c9, 0x0620ce9e},
+       {0xbd83a3da, 0xd3b69b29, 0xe02ce197, 0x9543950f, 0xc2f87783, 0x80799665, 0xc15be215, 0x11ce8199},
+       {0x1b29736e, 0x8f267f19, 0x1d5a0c3a, 0xa2e04d58, 0x1ae99514, 0x76803064, 0x57f7c806, 0x12129439},
+       {0xf32d6bac, 0xa0b973d4, 0xf0d81b72, 0xae951889, 0x2e2daa0a, 0x51dbe098, 0x40d9af8f, 0x04679474},
+       {0x22df9f13, 0x56313de8, 0x599e7536, 0xe2e75200, 0x6d163e50, 0xa1b4fce7, 0xc8111763, 0x0aec2172},
+       {0x355dd694, 0x4258374d, 0x44c76a20, 0x5c31e8ac, 0xaa5fd062, 0x9b473969, 0x1a37b6b4, 0x0a693d77},
+       {0x44ddbbdc, 0xbafb92a6, 0x26b01974, 0x63c7a02d, 0x5f28a274, 0x0ff86e13, 0x867f2e29, 0x0a7b462a},
+       {0xd5fba57b, 0x90684fea, 0xe0defe98, 0xed237883, 0x030ae924, 0xc502b692, 0xe7a1ec2c, 0x08aa58e8},
+       {0x5e9020dd, 0xade9d4b4, 0x87db8813, 0x489259d2, 0x25051238, 0x5ddce740, 0xb5bc4d11, 0x0c775db1},
+       {0x293f8481, 0xd52cc17a, 0x6f133205, 0x041178fb, 0xb2961832, 0xbbc70d18, 0x481760cd, 0x073d34d1},
+       {0xfdacff58, 0x8215b91d, 0x98331645, 0xd8d9177d, 0x439e803c, 0xe85223ad, 0xcca42c1f, 0x04aa8ef0},
+       {0x01ab3a4d, 0x006f60fa, 0x814ba450, 0xe6600e15, 0xdf9eb147, 0xbde4df36, 0x33760d7b, 0x055d58fa},
+       {0xec2a895e, 0x476ef4a4, 0x63e3f04a, 0x9b506ee3, 0xd1a8a12f, 0x60c69477, 0x0cb92cc1, 0x11d4b7f6}}};
+
+    static constexpr storage_array<omegas_count, limbs_count> omega_inv = {
+      {{0x00000000, 0x0a118000, 0xd0000001, 0x59aa76fe, 0x5c37b001, 0x60b44d1e, 0x9a2ca556, 0x12ab655e},
+       {0x00000000, 0x7af74000, 0x1fffffff, 0x8a442f99, 0xc529c400, 0x3cc739d6, 0x9a2ca556, 0x12ab655e},
+       {0xd60fb046, 0xc9fa190c, 0xc5b4674e, 0xdb5c179b, 0xbc7b8726, 0x2b2bce0b, 0xbf6e69bf, 0x0e4eb338},
+       {0x8ffc4ed5, 0x74732d1f, 0xb7f2eefc, 0x42d9f590, 0xa24dd4dd, 0xf70461e5, 0xef64676f, 0x03b6eba4},
+       {0x102bbab0, 0x5a21f98a, 0x8d8e2efb, 0xa6a147a9, 0x7612906f, 0x0eb4f005, 0x47d8d2e3, 0x0e1a5481},
+       {0xd01e5aa8, 0x6e509add, 0x6e3f123d, 0xe1582468, 0x8274db24, 0xbd6313ee, 0xd173a634, 0x05d5836e},
+       {0xe975c0cf, 0x6aab3344, 0x6f1dc38e, 0xca362e0e, 0x1dd1743a, 0x2fe72cda, 0xc1b4c4c2, 0x0c1c956e},
+       {0xec89a64f, 0x59fe97a0, 0xe8de5d4c, 0x579617d7, 0xc9c1ea7b, 0x256a305b, 0x53fa131b, 0x01ffae4e},
+       {0x29bcb088, 0x463a73ff, 0xe1438e80, 0xee9e9a5e, 0x3c9369e4, 0x2a00951f, 0x80a32052, 0x09711183},
+       {0x4bec8dd2, 0xa36899db, 0x96393687, 0x2946872e, 0x842df3c8, 0xd4b5734f, 0x5f5cd8fb, 0x0834098f},
+       {0xe3c711b9, 0x4bc485f6, 0x648d1d7e, 0xf43a2598, 0xee88abaa, 0x7f981a0e, 0xec6a3f27, 0x0c88c9c3},
+       {0x49046b52, 0x42bcc6c2, 0x56ab9ecc, 0xcc77294a, 0xe4df3ddd, 0x02ecb41a, 0x67f76726, 0x0e567d22},
+       {0x91c64fc2, 0x1cc56cc3, 0xd16a490b, 0x8cb71e65, 0x14fac366, 0x984be37e, 0xa25d7ba5, 0x0a08e032},
+       {0xd4f5941e, 0x966d9739, 0xe5772a73, 0x5805deb6, 0x5c1f970c, 0xe4eb0d33, 0xbdf35409, 0x039715db},
+       {0xcc6518ac, 0x8419686c, 0x9c7a2366, 0x96dec3a8, 0x71724384, 0xefbfcac6, 0xaf34c239, 0x0c44b99a},
+       {0xc18ff4fd, 0xcb66fe1b, 0x86c8d586, 0x588e18b3, 0x1dfab57c, 0xc6e6d2a3, 0x7d7d4efd, 0x10918ad2},
+       {0x97a18f58, 0x56d6cf22, 0xd0d7abd9, 0x11710758, 0x5eb7a9c5, 0xd1a6608b, 0xc4937e38, 0x04059bdb},
+       {0x4b1b63a9, 0x12998cbc, 0xcf420c9f, 0x0f780c6c, 0x129289ad, 0xa5e48723, 0x240a141d, 0x0a3a1223},
+       {0x00db2b48, 0xa43c0e02, 0x933d10ee, 0x76585489, 0xc0ba6a80, 0x12d64af1, 0x2fad8d8e, 0x01940f43},
+       {0x1d75bec9, 0xe29ef6c0, 0xd4b0183b, 0xead287a2, 0xedfd3795, 0x75a017cf, 0x64427c8e, 0x107f8d0f},
+       {0xa26c8c12, 0xa6f4e1d1, 0xf6610f7e, 0x13571553, 0x56701caf, 0xd95e5df6, 0x2263d69d, 0x050e7b89},
+       {0xc161761f, 0x271d7caf, 0xc369a371, 0xf1001d6f, 0x00e60f51, 0x65286415, 0xb74d14b8, 0x00b918f9},
+       {0x03ad3139, 0x01d3f431, 0xa137ce16, 0xe56f6002, 0x1deb42e8, 0x97f53369, 0xaa37cddd, 0x033fa9ac},
+       {0x60cf1330, 0x840f913b, 0x1df5ed87, 0x5610cde6, 0x72b36ddf, 0x858381b0, 0x6f64e0b7, 0x109bf66c},
+       {0x930cee0b, 0x432d3626, 0xf26e8ba3, 0x55ed3efb, 0x14c5457f, 0x802eebcc, 0xe2310f22, 0x00d300e3},
+       {0x4b9ac952, 0x3d29f5ba, 0xc8ea8f94, 0x7c7f2662, 0xcefc3052, 0x736ccb63, 0x0981f3cb, 0x04bfce2f},
+       {0x5d4e643c, 0x3da791ea, 0x85bff013, 0xb6a956ef, 0xd73de6a3, 0x86c629a8, 0x6b8c48a9, 0x0a5a5f55},
+       {0x49c6284a, 0x9ba6aa00, 0xeacbdc63, 0x0b8429fb, 0xedafdf37, 0x9b9c6c5b, 0xad0c78c6, 0x009907e8},
+       {0x3e47b53f, 0x50380ce2, 0x3a9613fc, 0x6ea3c2d3, 0x4c87ab50, 0xfe743105, 0xd192221c, 0x07871979},
+       {0xe978594b, 0x4ddd3320, 0x3abe3f79, 0xe5f36fbe, 0xe4dcff8e, 0x5dba9ef2, 0x7105148f, 0x0bfc27e2},
+       {0x498fb549, 0xd5993cd5, 0x09da9272, 0x718adcee, 0x72bd5bc0, 0x9e03cbb4, 0xc592813f, 0x07206942},
+       {0x78fd3239, 0xaf29730b, 0x40c3e723, 0xbd907ac9, 0x77f214f7, 0x5dcc0aad, 0xb05fb3a1, 0x02d958da},
+       {0xdf80223d, 0x55f432c9, 0x11a2fed9, 0x23daf2f6, 0x41ae8c34, 0x9e43e003, 0x95f22373, 0x0d51533b},
+       {0x7998b62c, 0xbb53132b, 0x22c9b4aa, 0x064a9186, 0x71d61334, 0xd56de253, 0x04e416f6, 0x10fcf25f},
+       {0xdddb58ec, 0x41f8042f, 0x10886d85, 0x7dd54384, 0x622ff4b4, 0x19544f90, 0x050cc539, 0x02f0b49a},
+       {0xa39b02a3, 0x8a3de898, 0xdc94422c, 0x068b2992, 0xf493db31, 0x1c5f019a, 0x11b0f668, 0x066b1790},
+       {0x78500f1a, 0x98310dd7, 0x735ccb27, 0x1c6050bf, 0xb2081df4, 0x07b6fa7f, 0xfa0f1e20, 0x003edf24},
+       {0x89b0ca6f, 0xb4d938e2, 0x2c897570, 0x0214eb59, 0x2d4cf27a, 0x56c45327, 0x3ed546a4, 0x10a2f358},
+       {0xef01ed78, 0xf2828212, 0xf103c9ca, 0xa66094ac, 0x7a2d5573, 0xdceb481d, 0x8af46aab, 0x0190fcde},
+       {0x526bf9fc, 0x023031cc, 0x79c209ba, 0x0e4136c0, 0x3ec42e5c, 0xe5234df1, 0x1d455234, 0x00cb9592},
+       {0x33bf2a1c, 0x842b0c9c, 0xa29b9236, 0x1fd43c95, 0xc06795d3, 0x6b37a603, 0x0c1b712a, 0x00017b17},
+       {0xaf858193, 0x2b955be2, 0x5fb5e378, 0xa513d8be, 0xa326aeb9, 0x88c4ebeb, 0xf3d45990, 0x00c378e2},
+       {0x6464580f, 0x33e6c8c0, 0x3c4aa09f, 0x9d560eb3, 0xcc98f404, 0xb3f1a899, 0x8ca24b48, 0x012c1ea5},
+       {0xe3b4dc56, 0xa0594a67, 0x91b698e1, 0xc8e6b582, 0x8df78057, 0x711cadbf, 0x396466f8, 0x0049abdf},
+       {0x4ffa086a, 0xecc89610, 0xca06afc6, 0x4db82291, 0x8f3a6426, 0x9ae7c68c, 0x2a874432, 0x0b3dae8c},
+       {0x3b3625b6, 0x1e62401f, 0x28471e5a, 0xd0692164, 0x5cad6b77, 0xb85aa9ec, 0xaa95acf2, 0x063e4b66},
+       {0xb9112c51, 0x2542c2b2, 0x6e23b3ce, 0x36ead8da, 0x76476754, 0x9a268d13, 0xa1ad7cf1, 0x121f44ad}}};
+
+    static constexpr storage_array<omegas_count, limbs_count> inv = {
+      {{0x00000001, 0x8508c000, 0x68000000, 0xacd53b7f, 0x2e1bd800, 0x305a268f, 0x4d1652ab, 0x0955b2af},
+       {0x00000001, 0xc78d2000, 0x1c000000, 0x033fd93f, 0xc529c401, 0xc88739d6, 0xf3a17c00, 0x0e008c06},
+       {0x00000001, 0xe8cf5000, 0xf6000000, 0x2e75281e, 0x90b0ba01, 0x949dc37a, 0xc6e710ab, 0x1055f8b2},
+       {0x00000001, 0xf9706800, 0xe3000000, 0x440fcf8e, 0x76743501, 0xfaa9084c, 0xb089db00, 0x1180af08},
+       {0x00000001, 0x01c0f400, 0xd9800001, 0x4edd2346, 0x6955f281, 0xadaeaab5, 0xa55b402b, 0x12160a33},
+       {0x00000001, 0x05e93a00, 0xd4c00001, 0x5443cd22, 0xe2c6d141, 0x07317be9, 0x1fc3f2c1, 0x1260b7c9},
+       {0x00000001, 0x07fd5d00, 0xd2600001, 0x56f72210, 0x1f7f40a1, 0xb3f2e484, 0xdcf84c0b, 0x12860e93},
+       {0x00000001, 0x09076e80, 0xd1300001, 0x5850cc87, 0x3ddb7851, 0x0a5398d1, 0x3b9278b1, 0x1298b9f9},
+       {0x00000001, 0x098c7740, 0x50980001, 0x58fda1c3, 0xcd099429, 0xb583f2f7, 0xeadf8f03, 0x12a20fab},
+       {0x00000001, 0x09cefba0, 0x104c0001, 0x59540c61, 0x14a0a215, 0x0b1c200b, 0x42861a2d, 0x12a6ba85},
+       {0x00000001, 0x09f03dd0, 0xf0260001, 0x597f41af, 0xb86c290b, 0xb5e83694, 0xee595fc1, 0x12a90ff1},
+       {0x00000001, 0x0a00dee8, 0x60130001, 0x5994dc57, 0x8a51ec86, 0x0b4e41d9, 0x4443028c, 0x12aa3aa8},
+       {0x00000001, 0x0a092f74, 0x18098001, 0xd99fa9ab, 0xf344ce43, 0x3601477b, 0x6f37d3f1, 0x12aad003},
+       {0x00000001, 0x0a0d57ba, 0xf404c001, 0x99a51054, 0x27be3f22, 0xcb5aca4d, 0x04b23ca3, 0x12ab1ab1},
+       {0x00000001, 0x0a0f6bdd, 0xe2026001, 0xf9a7c3a9, 0xc1faf791, 0x16078bb5, 0xcf6f70fd, 0x12ab4007},
+       {0x80000001, 0x0a1075ee, 0x59013001, 0xa9a91d54, 0x0f1953c9, 0xbb5dec6a, 0x34ce0b29, 0x12ab52b3},
+       {0x40000001, 0x0a10faf7, 0x94809801, 0x81a9ca29, 0x35a881e5, 0x0e091cc4, 0xe77d5840, 0x12ab5c08},
+       {0xa0000001, 0x0a113d7b, 0x32404c01, 0x6daa2094, 0x48f018f3, 0x375eb4f1, 0xc0d4fecb, 0x12ab60b3},
+       {0xd0000001, 0x0a115ebd, 0x81202601, 0x63aa4bc9, 0xd293e47a, 0xcc098107, 0x2d80d210, 0x12ab6309},
+       {0xe8000001, 0x0a116f5e, 0x28901301, 0xdeaa6164, 0x1765ca3d, 0x965ee713, 0xe3d6bbb3, 0x12ab6433},
+       {0x74000001, 0x0a1177af, 0x7c480981, 0x9c2a6c31, 0xb9cebd1f, 0xfb899a18, 0x3f01b084, 0x12ab64c9},
+       {0xba000001, 0x0a117bd7, 0x262404c1, 0x7aea7198, 0x8b033690, 0xae1ef39b, 0xec972aed, 0x12ab6513},
+       {0xdd000001, 0x0a117deb, 0x7b120261, 0xea4a744b, 0xf39d7348, 0x0769a05c, 0x4361e822, 0x12ab6539},
+       {0xee800001, 0x0a117ef5, 0x25890131, 0x21fa75a5, 0xa7ea91a5, 0x340ef6bd, 0xeec746bc, 0x12ab654b},
+       {0xf7400001, 0x0a117f7a, 0xfac48099, 0x3dd27651, 0x021120d3, 0x4a61a1ee, 0x4479f609, 0x12ab6555},
+       {0x7ba00001, 0x0a117fbd, 0x6562404d, 0x4bbe76a8, 0x2f24686a, 0xd58af786, 0xef534daf, 0x12ab6559},
+       {0xbdd00001, 0x0a117fde, 0x9ab12027, 0xd2b476d3, 0x45ae0c35, 0x1b1fa252, 0x44bff983, 0x12ab655c},
+       {0x5ee80001, 0x0a117fef, 0x35589014, 0x962f76e9, 0x50f2de1b, 0xbde9f7b8, 0x6f764f6c, 0x12ab655d},
+       {0xaf740001, 0x8a117ff7, 0x02ac480a, 0x77ecf6f4, 0x5695470e, 0x8f4f226b, 0x04d17a61, 0x12ab655e},
+       {0xd7ba0001, 0xca117ffb, 0x69562405, 0xe8cbb6f9, 0xd9667b87, 0xf801b7c4, 0x4f7f0fdb, 0x12ab655e},
+       {0xebdd0001, 0x6a117ffd, 0x1cab1203, 0xa13b16fc, 0x9acf15c4, 0x2c5b0271, 0x74d5da99, 0x12ab655e},
+       {0xf5ee8001, 0x3a117ffe, 0x76558902, 0xfd72c6fd, 0xfb8362e2, 0xc687a7c7, 0x87813ff7, 0x12ab655e},
+       {0x7af74001, 0xa2117fff, 0x232ac481, 0x2b8e9efe, 0x2bdd8972, 0x139dfa73, 0x90d6f2a7, 0x12ab655e},
+       {0xbd7ba001, 0x56117fff, 0x79956241, 0xc29c8afe, 0xc40a9cb9, 0xba2923c8, 0x9581cbfe, 0x12ab655e},
+       {0xdebdd001, 0x30117fff, 0xa4cab121, 0x8e2380fe, 0x9021265d, 0x8d6eb873, 0x97d738aa, 0x12ab655e},
+       {0xef5ee801, 0x1d117fff, 0xba655891, 0x73e6fbfe, 0xf62c6b2f, 0x771182c8, 0x9901ef00, 0x12ab655e},
+       {0xf7af7401, 0x13917fff, 0xc532ac49, 0x66c8b97e, 0xa9320d98, 0x6be2e7f3, 0x99974a2b, 0x12ab655e},
+       {0xfbd7ba01, 0x0ed17fff, 0xca995625, 0xe039983e, 0x02b4decc, 0xe64b9a89, 0x99e1f7c0, 0x12ab655e},
+       {0xfdebdd01, 0x0c717fff, 0xcd4cab13, 0x1cf2079e, 0xaf764767, 0xa37ff3d3, 0x9a074e8b, 0x12ab655e},
+       {0xfef5ee81, 0x0b417fff, 0xcea6558a, 0x3b4e3f4e, 0x05d6fbb4, 0x021a2079, 0x9a19f9f1, 0x12ab655e},
+       {0xff7af741, 0x8aa97fff, 0xcf532ac5, 0xca7c5b26, 0xb10755da, 0xb16736cb, 0x9a234fa3, 0x12ab655e},
+       {0xffbd7ba1, 0x4a5d7fff, 0xcfa99563, 0x12136912, 0x069f82ee, 0x090dc1f5, 0x9a27fa7d, 0x12ab655e},
+       {0xffdebdd1, 0x2a377fff, 0xcfd4cab2, 0xb5def008, 0xb16b9977, 0xb4e10789, 0x9a2a4fe9, 0x12ab655e},
+       {0xffef5ee9, 0x9a247fff, 0xcfea6559, 0x87c4b383, 0x06d1a4bc, 0x0acaaa54, 0x9a2b7aa0, 0x12ab655e},
+       {0xfff7af75, 0x521affff, 0x4ff532ad, 0xf0b79541, 0x3184aa5e, 0x35bf7bb9, 0x9a2c0ffb, 0x12ab655e},
+       {0xfffbd7bb, 0x2e163fff, 0x0ffa9957, 0x25310620, 0xc6de2d30, 0xcb39e46b, 0x9a2c5aa8, 0x12ab655e},
+       {0xfffdebde, 0x1c13dfff, 0x6ffd4cac, 0xbf6dbe8f, 0x118aee98, 0x95f718c5, 0x9a2c7fff, 0x12ab655e}}};
+  };
+} // namespace bls12_377
+
+#endif

icicle/include/fields/snark_fields/bls12_381_base.cuh

@@ -0,0 +1,61 @@
+#pragma once
+#ifndef BLS12_381_BASE_PARAMS_H
+#define BLS12_381_BASE_PARAMS_H
+
+#include "fields/storage.cuh"
+
+namespace bls12_381 {
+  struct fq_config {
+    static constexpr unsigned limbs_count = 12;
+    static constexpr unsigned modulus_bit_count = 381;
+    static constexpr unsigned num_of_reductions = 1;
+    static constexpr storage<limbs_count> modulus = {0xffffaaab, 0xb9feffff, 0xb153ffff, 0x1eabfffe,
+                                                     0xf6b0f624, 0x6730d2a0, 0xf38512bf, 0x64774b84,
+                                                     0x434bacd7, 0x4b1ba7b6, 0x397fe69a, 0x1a0111ea};
+    static constexpr storage<limbs_count> modulus_2 = {0xffff5556, 0x73fdffff, 0x62a7ffff, 0x3d57fffd,
+                                                       0xed61ec48, 0xce61a541, 0xe70a257e, 0xc8ee9709,
+                                                       0x869759ae, 0x96374f6c, 0x72ffcd34, 0x340223d4};
+    static constexpr storage<limbs_count> modulus_4 = {0xfffeaaac, 0xe7fbffff, 0xc54ffffe, 0x7aaffffa,
+                                                       0xdac3d890, 0x9cc34a83, 0xce144afd, 0x91dd2e13,
+                                                       0x0d2eb35d, 0x2c6e9ed9, 0xe5ff9a69, 0x680447a8};
+    static constexpr storage<limbs_count> neg_modulus = {0x00005555, 0x46010000, 0x4eac0000, 0xe1540001,
+                                                         0x094f09db, 0x98cf2d5f, 0x0c7aed40, 0x9b88b47b,
+                                                         0xbcb45328, 0xb4e45849, 0xc6801965, 0xe5feee15};
+    static constexpr storage<2 * limbs_count> modulus_wide = {
+      0xffffaaab, 0xb9feffff, 0xb153ffff, 0x1eabfffe, 0xf6b0f624, 0x6730d2a0, 0xf38512bf, 0x64774b84,
+      0x434bacd7, 0x4b1ba7b6, 0x397fe69a, 0x1a0111ea, 0x00000000, 0x00000000, 0x00000000, 0x00000000,
+      0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000};
+    static constexpr storage<2 * limbs_count> modulus_squared = {
+      0x1c718e39, 0x26aa0000, 0x76382eab, 0x7ced6b1d, 0x62113cfd, 0x162c3383, 0x3e71b743, 0x66bf91ed,
+      0x7091a049, 0x292e85a8, 0x86185c7b, 0x1d68619c, 0x0978ef01, 0xf5314933, 0x16ddca6e, 0x50a62cfd,
+      0x349e8bd0, 0x66e59e49, 0x0e7046b4, 0xe2dc90e5, 0xa22f25e9, 0x4bd278ea, 0xb8c35fc7, 0x02a437a4};
+    static constexpr storage<2 * limbs_count> modulus_squared_2 = {
+      0x38e31c72, 0x4d540000, 0xec705d56, 0xf9dad63a, 0xc42279fa, 0x2c586706, 0x7ce36e86, 0xcd7f23da,
+      0xe1234092, 0x525d0b50, 0x0c30b8f6, 0x3ad0c339, 0x12f1de02, 0xea629266, 0x2dbb94dd, 0xa14c59fa,
+      0x693d17a0, 0xcdcb3c92, 0x1ce08d68, 0xc5b921ca, 0x445e4bd3, 0x97a4f1d5, 0x7186bf8e, 0x05486f49};
+    static constexpr storage<2 * limbs_count> modulus_squared_4 = {
+      0x71c638e4, 0x9aa80000, 0xd8e0baac, 0xf3b5ac75, 0x8844f3f5, 0x58b0ce0d, 0xf9c6dd0c, 0x9afe47b4,
+      0xc2468125, 0xa4ba16a1, 0x186171ec, 0x75a18672, 0x25e3bc04, 0xd4c524cc, 0x5b7729bb, 0x4298b3f4,
+      0xd27a2f41, 0x9b967924, 0x39c11ad1, 0x8b724394, 0x88bc97a7, 0x2f49e3aa, 0xe30d7f1d, 0x0a90de92};
+    static constexpr storage<limbs_count> m = {0xd59646e8, 0xec4f881f, 0x8163c701, 0x4e65c59e, 0x80a19de7, 0x2f7d1dc7,
+                                               0x7fda82a5, 0xa46e09d0, 0x331e9ae8, 0x38a0406c, 0xcf327917, 0x2760d74b};
+    static constexpr storage<limbs_count> one = {0x00000001, 0x00000000, 0x00000000, 0x00000000,
+                                                 0x00000000, 0x00000000, 0x00000000, 0x00000000,
+                                                 0x00000000, 0x00000000, 0x00000000, 0x00000000};
+    static constexpr storage<limbs_count> zero = {0x00000000, 0x00000000, 0x00000000, 0x00000000,
+                                                  0x00000000, 0x00000000, 0x00000000, 0x00000000,
+                                                  0x00000000, 0x00000000, 0x00000000, 0x00000000};
+    static constexpr storage<limbs_count> montgomery_r = {0x0002fffd, 0x76090000, 0xc40c0002, 0xebf4000b,
+                                                          0x53c758ba, 0x5f489857, 0x70525745, 0x77ce5853,
+                                                          0xa256ec6d, 0x5c071a97, 0xfa80e493, 0x15f65ec3};
+    static constexpr storage<limbs_count> montgomery_r_inv = {0x380b4820, 0xf4d38259, 0xd898fafb, 0x7fe11274,
+                                                              0x14956dc8, 0x343ea979, 0x58a88de9, 0x1797ab14,
+                                                              0x3c4f538b, 0xed5e6427, 0xe8fb0ce9, 0x14fec701};
+    // nonresidue to generate the extension field
+    static constexpr uint32_t nonresidue = 1;
+    // true if nonresidue is negative
+    static constexpr bool nonresidue_is_negative = true;
+  };
+} // namespace bls12_381
+
+#endif

icicle/include/fields/snark_fields/bls12_381_scalar.cuh

@@ -1,8 +1,8 @@
 #pragma once
-#ifndef BLS12_381_PARAMS_H
-#define BLS12_381_PARAMS_H
+#ifndef BLS12_381_SCALAR_PARAMS_H
+#define BLS12_381_SCALAR_PARAMS_H
 
-#include "utils/storage.cuh"
+#include "fields/storage.cuh"
 
 namespace bls12_381 {
   struct fp_config {
@@ -145,88 +145,6 @@ namespace bls12_381 {
        {0x00000003, 0x00034801, 0x588313f9, 0x4079f3f8, 0xa32e27f5, 0xdffedd77, 0x41c22ea1, 0x73eda752},
        {0x00000002, 0x0001a400, 0xac40b7fc, 0x4a1bcbfd, 0xd667fffd, 0x099c5abf, 0xb5afd5f5, 0x73eda752}}};
   };
-
-  struct fq_config {
-    static constexpr unsigned limbs_count = 12;
-    static constexpr unsigned modulus_bit_count = 381;
-    static constexpr unsigned num_of_reductions = 1;
-    static constexpr storage<limbs_count> modulus = {0xffffaaab, 0xb9feffff, 0xb153ffff, 0x1eabfffe,
-                                                     0xf6b0f624, 0x6730d2a0, 0xf38512bf, 0x64774b84,
-                                                     0x434bacd7, 0x4b1ba7b6, 0x397fe69a, 0x1a0111ea};
-    static constexpr storage<limbs_count> modulus_2 = {0xffff5556, 0x73fdffff, 0x62a7ffff, 0x3d57fffd,
-                                                       0xed61ec48, 0xce61a541, 0xe70a257e, 0xc8ee9709,
-                                                       0x869759ae, 0x96374f6c, 0x72ffcd34, 0x340223d4};
-    static constexpr storage<limbs_count> modulus_4 = {0xfffeaaac, 0xe7fbffff, 0xc54ffffe, 0x7aaffffa,
-                                                       0xdac3d890, 0x9cc34a83, 0xce144afd, 0x91dd2e13,
-                                                       0x0d2eb35d, 0x2c6e9ed9, 0xe5ff9a69, 0x680447a8};
-    static constexpr storage<limbs_count> neg_modulus = {0x00005555, 0x46010000, 0x4eac0000, 0xe1540001,
-                                                         0x094f09db, 0x98cf2d5f, 0x0c7aed40, 0x9b88b47b,
-                                                         0xbcb45328, 0xb4e45849, 0xc6801965, 0xe5feee15};
-    static constexpr storage<2 * limbs_count> modulus_wide = {
-      0xffffaaab, 0xb9feffff, 0xb153ffff, 0x1eabfffe, 0xf6b0f624, 0x6730d2a0, 0xf38512bf, 0x64774b84,
-      0x434bacd7, 0x4b1ba7b6, 0x397fe69a, 0x1a0111ea, 0x00000000, 0x00000000, 0x00000000, 0x00000000,
-      0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000};
-    static constexpr storage<2 * limbs_count> modulus_squared = {
-      0x1c718e39, 0x26aa0000, 0x76382eab, 0x7ced6b1d, 0x62113cfd, 0x162c3383, 0x3e71b743, 0x66bf91ed,
-      0x7091a049, 0x292e85a8, 0x86185c7b, 0x1d68619c, 0x0978ef01, 0xf5314933, 0x16ddca6e, 0x50a62cfd,
-      0x349e8bd0, 0x66e59e49, 0x0e7046b4, 0xe2dc90e5, 0xa22f25e9, 0x4bd278ea, 0xb8c35fc7, 0x02a437a4};
-    static constexpr storage<2 * limbs_count> modulus_squared_2 = {
-      0x38e31c72, 0x4d540000, 0xec705d56, 0xf9dad63a, 0xc42279fa, 0x2c586706, 0x7ce36e86, 0xcd7f23da,
-      0xe1234092, 0x525d0b50, 0x0c30b8f6, 0x3ad0c339, 0x12f1de02, 0xea629266, 0x2dbb94dd, 0xa14c59fa,
-      0x693d17a0, 0xcdcb3c92, 0x1ce08d68, 0xc5b921ca, 0x445e4bd3, 0x97a4f1d5, 0x7186bf8e, 0x05486f49};
-    static constexpr storage<2 * limbs_count> modulus_squared_4 = {
-      0x71c638e4, 0x9aa80000, 0xd8e0baac, 0xf3b5ac75, 0x8844f3f5, 0x58b0ce0d, 0xf9c6dd0c, 0x9afe47b4,
-      0xc2468125, 0xa4ba16a1, 0x186171ec, 0x75a18672, 0x25e3bc04, 0xd4c524cc, 0x5b7729bb, 0x4298b3f4,
-      0xd27a2f41, 0x9b967924, 0x39c11ad1, 0x8b724394, 0x88bc97a7, 0x2f49e3aa, 0xe30d7f1d, 0x0a90de92};
-    static constexpr storage<limbs_count> m = {0xd59646e8, 0xec4f881f, 0x8163c701, 0x4e65c59e, 0x80a19de7, 0x2f7d1dc7,
-                                               0x7fda82a5, 0xa46e09d0, 0x331e9ae8, 0x38a0406c, 0xcf327917, 0x2760d74b};
-    static constexpr storage<limbs_count> one = {0x00000001, 0x00000000, 0x00000000, 0x00000000,
-                                                 0x00000000, 0x00000000, 0x00000000, 0x00000000,
-                                                 0x00000000, 0x00000000, 0x00000000, 0x00000000};
-    static constexpr storage<limbs_count> zero = {0x00000000, 0x00000000, 0x00000000, 0x00000000,
-                                                  0x00000000, 0x00000000, 0x00000000, 0x00000000,
-                                                  0x00000000, 0x00000000, 0x00000000, 0x00000000};
-    static constexpr storage<limbs_count> montgomery_r = {0x0002fffd, 0x76090000, 0xc40c0002, 0xebf4000b,
-                                                          0x53c758ba, 0x5f489857, 0x70525745, 0x77ce5853,
-                                                          0xa256ec6d, 0x5c071a97, 0xfa80e493, 0x15f65ec3};
-    static constexpr storage<limbs_count> montgomery_r_inv = {0x380b4820, 0xf4d38259, 0xd898fafb, 0x7fe11274,
-                                                              0x14956dc8, 0x343ea979, 0x58a88de9, 0x1797ab14,
-                                                              0x3c4f538b, 0xed5e6427, 0xe8fb0ce9, 0x14fec701};
-    // i^2, the square of the imaginary unit for the extension field
-    static constexpr uint32_t i_squared = 1;
-    // true if i^2 is negative
-    static constexpr bool i_squared_is_negative = true;
-  };
-
-  // G1 and G2 generators
-  static constexpr storage<fq_config::limbs_count> g1_gen_x = {0xdb22c6bb, 0xfb3af00a, 0xf97a1aef, 0x6c55e83f,
-                                                               0x171bac58, 0xa14e3a3f, 0x9774b905, 0xc3688c4f,
-                                                               0x4fa9ac0f, 0x2695638c, 0x3197d794, 0x17f1d3a7};
-  static constexpr storage<fq_config::limbs_count> g1_gen_y = {0x46c5e7e1, 0x0caa2329, 0xa2888ae4, 0xd03cc744,
-                                                               0x2c04b3ed, 0x00db18cb, 0xd5d00af6, 0xfcf5e095,
-                                                               0x741d8ae4, 0xa09e30ed, 0xe3aaa0f1, 0x08b3f481};
-  static constexpr storage<fq_config::limbs_count> g2_gen_x_re = {0xc121bdb8, 0xd48056c8, 0xa805bbef, 0x0bac0326,
-                                                                  0x7ae3d177, 0xb4510b64, 0xfa403b02, 0xc6e47ad4,
-                                                                  0x2dc51051, 0x26080527, 0xf08f0a91, 0x024aa2b2};
-  static constexpr storage<fq_config::limbs_count> g2_gen_x_im = {0x5d042b7e, 0xe5ac7d05, 0x13945d57, 0x334cf112,
-                                                                  0xdc7f5049, 0xb5da61bb, 0x9920b61a, 0x596bd0d0,
-                                                                  0x88274f65, 0x7dacd3a0, 0x52719f60, 0x13e02b60};
-  static constexpr storage<fq_config::limbs_count> g2_gen_y_re = {0x08b82801, 0xe1935486, 0x3baca289, 0x923ac9cc,
-                                                                  0x5160d12c, 0x6d429a69, 0x8cbdd3a7, 0xadfd9baa,
-                                                                  0xda2e351a, 0x8cc9cdc6, 0x727d6e11, 0x0ce5d527};
-  static constexpr storage<fq_config::limbs_count> g2_gen_y_im = {0xf05f79be, 0xaaa9075f, 0x5cec1da1, 0x3f370d27,
-                                                                  0x572e99ab, 0x267492ab, 0x85a763af, 0xcb3e287e,
-                                                                  0x2bc28b99, 0x32acd2b0, 0x2ea734cc, 0x0606c4a0};
-
-  static constexpr storage<fq_config::limbs_count> weierstrass_b = {0x00000004, 0x00000000, 0x00000000, 0x00000000,
-                                                                    0x00000000, 0x00000000, 0x00000000, 0x00000000,
-                                                                    0x00000000, 0x00000000, 0x00000000, 0x00000000};
-  static constexpr storage<fq_config::limbs_count> weierstrass_b_g2_re = {
-    0x00000004, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000,
-    0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000};
-  static constexpr storage<fq_config::limbs_count> weierstrass_b_g2_im = {
-    0x00000004, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000,
-    0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000};
 } // namespace bls12_381
 
 #endif

icicle/include/fields/snark_fields/bn254_base.cuh

@@ -0,0 +1,49 @@
+#pragma once
+#ifndef BN254_BASE_PARAMS_H
+#define BN254_BASE_PARAMS_H
+
+#include "fields/storage.cuh"
+
+namespace bn254 {
+  struct fq_config {
+    static constexpr unsigned limbs_count = 8;
+    static constexpr unsigned modulus_bit_count = 254;
+    static constexpr unsigned num_of_reductions = 1;
+    static constexpr storage<limbs_count> modulus = {0xd87cfd47, 0x3c208c16, 0x6871ca8d, 0x97816a91,
+                                                     0x8181585d, 0xb85045b6, 0xe131a029, 0x30644e72};
+    static constexpr storage<limbs_count> modulus_2 = {0xb0f9fa8e, 0x7841182d, 0xd0e3951a, 0x2f02d522,
+                                                       0x0302b0bb, 0x70a08b6d, 0xc2634053, 0x60c89ce5};
+    static constexpr storage<limbs_count> modulus_4 = {0x61f3f51c, 0xf082305b, 0xa1c72a34, 0x5e05aa45,
+                                                       0x06056176, 0xe14116da, 0x84c680a6, 0xc19139cb};
+    static constexpr storage<limbs_count> neg_modulus = {0x278302b9, 0xc3df73e9, 0x978e3572, 0x687e956e,
+                                                         0x7e7ea7a2, 0x47afba49, 0x1ece5fd6, 0xcf9bb18d};
+    static constexpr storage<2 * limbs_count> modulus_wide = {
+      0xd87cfd47, 0x3c208c16, 0x6871ca8d, 0x97816a91, 0x8181585d, 0xb85045b6, 0xe131a029, 0x30644e72,
+      0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000};
+    static constexpr storage<2 * limbs_count> modulus_squared = {
+      0x275d69b1, 0x3b5458a2, 0x09eac101, 0xa602072d, 0x6d96cadc, 0x4a50189c, 0x7a1242c8, 0x04689e95,
+      0x34c6b38d, 0x26edfa5c, 0x16375606, 0xb00b8551, 0x0348d21c, 0x599a6f7c, 0x763cbf9c, 0x0925c4b8};
+    static constexpr storage<2 * limbs_count> modulus_squared_2 = {
+      0x4ebad362, 0x76a8b144, 0x13d58202, 0x4c040e5a, 0xdb2d95b9, 0x94a03138, 0xf4248590, 0x08d13d2a,
+      0x698d671a, 0x4ddbf4b8, 0x2c6eac0c, 0x60170aa2, 0x0691a439, 0xb334def8, 0xec797f38, 0x124b8970};
+    static constexpr storage<2 * limbs_count> modulus_squared_4 = {
+      0x9d75a6c4, 0xed516288, 0x27ab0404, 0x98081cb4, 0xb65b2b72, 0x29406271, 0xe8490b21, 0x11a27a55,
+      0xd31ace34, 0x9bb7e970, 0x58dd5818, 0xc02e1544, 0x0d234872, 0x6669bdf0, 0xd8f2fe71, 0x249712e1};
+    static constexpr storage<limbs_count> m = {0x19bf90e5, 0x6f3aed8a, 0x67cd4c08, 0xae965e17,
+                                               0x68073013, 0xab074a58, 0x623a04a7, 0x54a47462};
+    static constexpr storage<limbs_count> one = {0x00000001, 0x00000000, 0x00000000, 0x00000000,
+                                                 0x00000000, 0x00000000, 0x00000000, 0x00000000};
+    static constexpr storage<limbs_count> zero = {0x00000000, 0x00000000, 0x00000000, 0x00000000,
+                                                  0x00000000, 0x00000000, 0x00000000, 0x00000000};
+    static constexpr storage<limbs_count> montgomery_r = {0xc58f0d9d, 0xd35d438d, 0xf5c70b3d, 0x0a78eb28,
+                                                          0x7879462c, 0x666ea36f, 0x9a07df2f, 0x0e0a77c1};
+    static constexpr storage<limbs_count> montgomery_r_inv = {0x014afa37, 0xed84884a, 0x0278edf8, 0xeb202285,
+                                                              0xb74492d9, 0xcf63e9cf, 0x59e5c639, 0x2e671571};
+    // nonresidue to generate the extension field
+    static constexpr uint32_t nonresidue = 1;
+    // true if nonresidue is negative
+    static constexpr bool nonresidue_is_negative = true;
+  };
+} // namespace bn254
+
+#endif

icicle/include/fields/snark_fields/bn254_scalar.cuh

@@ -1,8 +1,8 @@
 #pragma once
-#ifndef BN254_PARAMS_H
-#define BN254_PARAMS_H
+#ifndef BN254_SCALAR_PARAMS_H
+#define BN254_SCALAR_PARAMS_H
 
-#include "utils/storage.cuh"
+#include "fields/storage.cuh"
 
 namespace bn254 {
   struct fp_config {
@@ -133,67 +133,6 @@ namespace bn254 {
        {0x73c14d83, 0x0cb3e36b, 0x733c6782, 0xf808dca3, 0x7778a18c, 0x921c407f, 0xd4a7d1cd, 0x30644e6c},
        {0xb1e0a6c2, 0xa84aec7f, 0xf67aec09, 0x101e6275, 0xfc7cfcf5, 0xa536431a, 0xdaecb8fb, 0x30644e6f}}};
   };
-
-  struct fq_config {
-    static constexpr unsigned limbs_count = 8;
-    static constexpr unsigned modulus_bit_count = 254;
-    static constexpr unsigned num_of_reductions = 1;
-    static constexpr storage<limbs_count> modulus = {0xd87cfd47, 0x3c208c16, 0x6871ca8d, 0x97816a91,
-                                                     0x8181585d, 0xb85045b6, 0xe131a029, 0x30644e72};
-    static constexpr storage<limbs_count> modulus_2 = {0xb0f9fa8e, 0x7841182d, 0xd0e3951a, 0x2f02d522,
-                                                       0x0302b0bb, 0x70a08b6d, 0xc2634053, 0x60c89ce5};
-    static constexpr storage<limbs_count> modulus_4 = {0x61f3f51c, 0xf082305b, 0xa1c72a34, 0x5e05aa45,
-                                                       0x06056176, 0xe14116da, 0x84c680a6, 0xc19139cb};
-    static constexpr storage<limbs_count> neg_modulus = {0x278302b9, 0xc3df73e9, 0x978e3572, 0x687e956e,
-                                                         0x7e7ea7a2, 0x47afba49, 0x1ece5fd6, 0xcf9bb18d};
-    static constexpr storage<2 * limbs_count> modulus_wide = {
-      0xd87cfd47, 0x3c208c16, 0x6871ca8d, 0x97816a91, 0x8181585d, 0xb85045b6, 0xe131a029, 0x30644e72,
-      0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000};
-    static constexpr storage<2 * limbs_count> modulus_squared = {
-      0x275d69b1, 0x3b5458a2, 0x09eac101, 0xa602072d, 0x6d96cadc, 0x4a50189c, 0x7a1242c8, 0x04689e95,
-      0x34c6b38d, 0x26edfa5c, 0x16375606, 0xb00b8551, 0x0348d21c, 0x599a6f7c, 0x763cbf9c, 0x0925c4b8};
-    static constexpr storage<2 * limbs_count> modulus_squared_2 = {
-      0x4ebad362, 0x76a8b144, 0x13d58202, 0x4c040e5a, 0xdb2d95b9, 0x94a03138, 0xf4248590, 0x08d13d2a,
-      0x698d671a, 0x4ddbf4b8, 0x2c6eac0c, 0x60170aa2, 0x0691a439, 0xb334def8, 0xec797f38, 0x124b8970};
-    static constexpr storage<2 * limbs_count> modulus_squared_4 = {
-      0x9d75a6c4, 0xed516288, 0x27ab0404, 0x98081cb4, 0xb65b2b72, 0x29406271, 0xe8490b21, 0x11a27a55,
-      0xd31ace34, 0x9bb7e970, 0x58dd5818, 0xc02e1544, 0x0d234872, 0x6669bdf0, 0xd8f2fe71, 0x249712e1};
-    static constexpr storage<limbs_count> m = {0x19bf90e5, 0x6f3aed8a, 0x67cd4c08, 0xae965e17,
-                                               0x68073013, 0xab074a58, 0x623a04a7, 0x54a47462};
-    static constexpr storage<limbs_count> one = {0x00000001, 0x00000000, 0x00000000, 0x00000000,
-                                                 0x00000000, 0x00000000, 0x00000000, 0x00000000};
-    static constexpr storage<limbs_count> zero = {0x00000000, 0x00000000, 0x00000000, 0x00000000,
-                                                  0x00000000, 0x00000000, 0x00000000, 0x00000000};
-    static constexpr storage<limbs_count> montgomery_r = {0xc58f0d9d, 0xd35d438d, 0xf5c70b3d, 0x0a78eb28,
-                                                          0x7879462c, 0x666ea36f, 0x9a07df2f, 0x0e0a77c1};
-    static constexpr storage<limbs_count> montgomery_r_inv = {0x014afa37, 0xed84884a, 0x0278edf8, 0xeb202285,
-                                                              0xb74492d9, 0xcf63e9cf, 0x59e5c639, 0x2e671571};
-    // i^2, the square of the imaginary unit for the extension field
-    static constexpr uint32_t i_squared = 1;
-    // true if i^2 is negative
-    static constexpr bool i_squared_is_negative = true;
-  };
-
-  // G1 and G2 generators
-  static constexpr storage<fq_config::limbs_count> g1_gen_x = {0x00000001, 0x00000000, 0x00000000, 0x00000000,
-                                                               0x00000000, 0x00000000, 0x00000000, 0x00000000};
-  static constexpr storage<fq_config::limbs_count> g1_gen_y = {0x00000002, 0x00000000, 0x00000000, 0x00000000,
-                                                               0x00000000, 0x00000000, 0x00000000, 0x00000000};
-  static constexpr storage<fq_config::limbs_count> g2_gen_x_re = {0xd992f6ed, 0x46debd5c, 0xf75edadd, 0x674322d4,
-                                                                  0x5e5c4479, 0x426a0066, 0x121f1e76, 0x1800deef};
-  static constexpr storage<fq_config::limbs_count> g2_gen_x_im = {0xaef312c2, 0x97e485b7, 0x35a9e712, 0xf1aa4933,
-                                                                  0x31fb5d25, 0x7260bfb7, 0x920d483a, 0x198e9393};
-  static constexpr storage<fq_config::limbs_count> g2_gen_y_re = {0x66fa7daa, 0x4ce6cc01, 0x0c43d37b, 0xe3d1e769,
-                                                                  0x8dcb408f, 0x4aab7180, 0xdb8c6deb, 0x12c85ea5};
-  static constexpr storage<fq_config::limbs_count> g2_gen_y_im = {0xd122975b, 0x55acdadc, 0x70b38ef3, 0xbc4b3133,
-                                                                  0x690c3395, 0xec9e99ad, 0x585ff075, 0x090689d0};
-
-  static constexpr storage<fq_config::limbs_count> weierstrass_b = {0x00000003, 0x00000000, 0x00000000, 0x00000000,
-                                                                    0x00000000, 0x00000000, 0x00000000, 0x00000000};
-  static constexpr storage<fq_config::limbs_count> weierstrass_b_g2_re = {
-    0x24a138e5, 0x3267e6dc, 0x59dbefa3, 0xb5b4c5e5, 0x1be06ac3, 0x81be1899, 0xceb8aaae, 0x2b149d40};
-  static constexpr storage<fq_config::limbs_count> weierstrass_b_g2_im = {
-    0x85c315d2, 0xe4a2bd06, 0xe52d1852, 0xa74fa084, 0xeed8fdf4, 0xcd2cafad, 0x3af0fed4, 0x009713b0};
 } // namespace bn254
 
 #endif

icicle/include/fields/snark_fields/bw6_761_base.cuh

@@ -1,13 +1,10 @@
 #pragma once
-#ifndef BW6_761_PARAMS_H
-#define BW6_761_PARAMS_H
+#ifndef BW6_761_BASE_BASE_H
+#define BW6_761_BASE_BASE_H
 
-#include "utils/storage.cuh"
-#include "bls12_377_params.cuh"
+#include "fields/storage.cuh"
 
 namespace bw6_761 {
-  typedef bls12_377::fq_config fp_config;
-
   struct fq_config {
     static constexpr unsigned limbs_count = 24;
     static constexpr unsigned modulus_bit_count = 761;
@@ -77,33 +74,6 @@ namespace bw6_761 {
       0x7695ef18, 0x5e763565, 0x4fae56bb, 0x226022c2, 0xb70d7652, 0x80e7f067, 0x72116b89, 0x435a8b4a,
       0x5d84e0d4, 0xac258fd6, 0x4427c7b2, 0x47ee8ac5, 0xd04e621b, 0x478c4048, 0x2add3e93, 0x00e0aa7d};
   };
-
-  // G1 and G2 generators
-  static constexpr storage<fq_config::limbs_count> g1_gen_x = {
-    0x66e5b43d, 0x4088f3af, 0xa6af603f, 0x055928ac, 0x56133e82, 0x6750dd03, 0x280ca27f, 0x03758f9a,
-    0xc9ea0971, 0x5bd71fa0, 0x47729b90, 0xa17a54ce, 0x94c2e746, 0x11dbfcd2, 0xc15520ac, 0x79017ffa,
-    0x85f56fc7, 0xee05c54b, 0x551b27f0, 0xe6a0cfb7, 0xa477beae, 0xb277ce98, 0x0ea190c8, 0x01075b02};
-  static constexpr storage<fq_config::limbs_count> g1_gen_y = {
-    0xb4e95363, 0xbafc8f2d, 0x0b20d2a1, 0xad1cb2be, 0xcad0fb93, 0xb2b08119, 0xb3053253, 0x9f9df141,
-    0x6fc2cdd4, 0xbe3fb90b, 0x717a4c55, 0xcc685d31, 0x71b5b806, 0xc5b8fa17, 0xaf7e0dba, 0x265909f1,
-    0xa2e573a3, 0x1a7348d2, 0x884c9ec6, 0x0f952589, 0x45cc2a42, 0xe6fd637b, 0x0a6fc574, 0x0058b84e};
-  static constexpr storage<fq_config::limbs_count> g2_gen_x = {
-    0xcd025f1c, 0xa830c194, 0xe1bf995b, 0x6410cf4f, 0xc2ad54b0, 0x00e96efb, 0x3cd208d7, 0xce6948cb,
-    0x00e1b6ba, 0x963317a3, 0xac70e7c7, 0xc5bbcae9, 0xf09feb58, 0x734ec3f1, 0xab3da268, 0x26b41c5d,
-    0x13890f6d, 0x4c062010, 0xc5a7115f, 0xd61053aa, 0x69d660f9, 0xc852a82e, 0x41d9b816, 0x01101332};
-  static constexpr storage<fq_config::limbs_count> g2_gen_y = {
-    0x28c73b61, 0xeb70a167, 0xf9eac689, 0x91ec0594, 0x3c5a02a5, 0x58aa2d3a, 0x504affc7, 0x3ea96fcd,
-    0xffa82300, 0x8906c170, 0xd2c712b8, 0x64f293db, 0x33293fef, 0x94c97eb7, 0x0b95a59c, 0x0a1d86c8,
-    0x53ffe316, 0x81a78e27, 0xcec2181c, 0x26b7cf9a, 0xe4b6d2dc, 0x8179eb10, 0x7761369f, 0x0017c335};
-
-  static constexpr storage<fq_config::limbs_count> weierstrass_b = {
-    0x0000008a, 0xf49d0000, 0x70000082, 0xe6913e68, 0xeaf0a437, 0x160cf8ae, 0x5667a8f8, 0x98a116c2,
-    0x73ebff2e, 0x71dcd3dc, 0x12f9fd90, 0x8689c8ed, 0x25b42304, 0x03cebaff, 0xe584e919, 0x707ba638,
-    0x8087be41, 0x528275ef, 0x81d14688, 0xb926186a, 0x04faff3e, 0xd187c940, 0xfb83ce0a, 0x0122e824};
-  static constexpr storage<fq_config::limbs_count> g2_weierstrass_b = {
-    0x00000004, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000,
-    0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000,
-    0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000};
 } // namespace bw6_761
 
-#endif
+#endif

icicle/include/fields/stark_fields/baby_bear.cuh

@@ -0,0 +1,52 @@
+#pragma once
+
+#include "fields/storage.cuh"
+#include "fields/field.cuh"
+
+namespace baby_bear {
+  struct fp_config {
+    static constexpr unsigned limbs_count = 1;
+    static constexpr unsigned omegas_count = 28;
+    static constexpr unsigned modulus_bit_count = 31;
+    static constexpr unsigned num_of_reductions = 1;
+
+    static constexpr storage<limbs_count> modulus = {0x78000001};
+    static constexpr storage<limbs_count> modulus_2 = {0xf0000002};
+    static constexpr storage<limbs_count> modulus_4 = {0x00000000};
+    static constexpr storage<limbs_count> neg_modulus = {0x87ffffff};
+    static constexpr storage<2 * limbs_count> modulus_wide = {0x78000001, 0x00000000};
+    static constexpr storage<2 * limbs_count> modulus_squared = {0xf0000001, 0x38400000};
+    static constexpr storage<2 * limbs_count> modulus_squared_2 = {0xe0000002, 0x70800001};
+    static constexpr storage<2 * limbs_count> modulus_squared_4 = {0xc0000004, 0xe1000003};
+
+    static constexpr storage<limbs_count> m = {0x88888887};
+    static constexpr storage<limbs_count> one = {0x00000001};
+    static constexpr storage<limbs_count> zero = {0x00000000};
+    static constexpr storage<limbs_count> montgomery_r = {0xffffffe};
+    static constexpr storage<limbs_count> montgomery_r_inv = {0x38400000};
+
+    static constexpr storage_array<omegas_count, limbs_count> omega = {
+      {{0x78000000}, {0x10faa3e0}, {0x6b615c47}, {0x21ceed5a}, {0x2c1c3348}, {0x36c54c86}, {0x701dd01c},
+       {0x56a9a28e}, {0x03e4cabf}, {0x5bacde79}, {0x1eb53838}, {0x1cd781af}, {0x0961a0b7}, {0x65098a87},
+       {0x77851a0b}, {0x5bcba331}, {0x053fc0f5}, {0x5bf816e5}, {0x4bb124ab}, {0x571e9d4e}, {0x313732cb},
+       {0x28aca172}, {0x4e319b52}, {0x45692d95}, {0x14ff4ba1}, {0x00004951}, {0x00000089}}};
+
+    static constexpr storage_array<omegas_count, limbs_count> omega_inv = {
+      {{0x78000000}, {0x67055c21}, {0x5ee99486}, {0x0bb4c4e4}, {0x4ab33b27}, {0x044b4497}, {0x410e23aa},
+       {0x08a7ee2b}, {0x563cb93d}, {0x3d70b4b7}, {0x77d999f1}, {0x6ceb65b5}, {0x49e7f635}, {0x0eae3a8c},
+       {0x238b8a78}, {0x70d71b0a}, {0x0eaacc45}, {0x5af0f193}, {0x47303308}, {0x573cbfad}, {0x29ff72c0},
+       {0x05af9dac}, {0x00ef24df}, {0x26985530}, {0x22d1ce4b}, {0x08359375}, {0x2cabe994}}};
+
+    static constexpr storage_array<omegas_count, limbs_count> inv = {
+      {{0x3c000001}, {0x5a000001}, {0x69000001}, {0x70800001}, {0x74400001}, {0x76200001}, {0x77100001},
+       {0x77880001}, {0x77c40001}, {0x77e20001}, {0x77f10001}, {0x77f88001}, {0x77fc4001}, {0x77fe2001},
+       {0x77ff1001}, {0x77ff8801}, {0x77ffc401}, {0x77ffe201}, {0x77fff101}, {0x77fff881}, {0x77fffc41},
+       {0x77fffe21}, {0x77ffff11}, {0x77ffff89}, {0x77ffffc5}, {0x77ffffe3}, {0x77fffff2}}};
+
+    // nonresidue to generate the extension field
+    static constexpr uint32_t nonresidue = 11;
+    // true if nonresidue is negative.
+    // TODO: we're very confused by plonky3 and risc0 having different nonresidues: 11 and -11 respectively
+    static constexpr bool nonresidue_is_negative = true;
+  };
+} // namespace baby_bear

icicle/include/gpu-utils/modifiers.cuh

@@ -0,0 +1,11 @@
+#if defined(DEVMODE) || defined(DEBUG)
+#define INLINE_MACRO
+#define UNROLL
+#else
+#define INLINE_MACRO __forceinline__
+#define UNROLL       #pragma unroll
+#endif
+
+#define HOST_INLINE        __host__ INLINE_MACRO
+#define DEVICE_INLINE      __device__ INLINE_MACRO
+#define HOST_DEVICE_INLINE __host__ __device__ INLINE_MACRO

icicle/include/gpu-utils/sharedmem.cuh

@@ -58,8 +58,6 @@
 #ifndef _SHAREDMEM_H_
 #define _SHAREDMEM_H_
 
-#include "curves/curve_config.cuh"
-
 /** @brief Wrapper class for templatized dynamic shared memory arrays.
  *
  * This struct uses template specialization on the type \a T to declare
@@ -77,8 +75,8 @@ struct SharedMemory {
   //! @returns Pointer to runtime-sized shared memory array
   __device__ T* getPointer()
   {
-    extern __device__ void Error_UnsupportedType(); // Ensure that we won't compile any un-specialized types
-    Error_UnsupportedType();
+    // extern __device__ void Error_UnsupportedType(); // Ensure that we won't compile any un-specialized types
+    // Error_UnsupportedType();
     return (T*)0;
   }
   // TODO: Use operator overloading to make this class look like a regular array
@@ -214,24 +212,6 @@ struct SharedMemory<uchar4> {
   }
 };
 
-template <>
-struct SharedMemory<curve_config::scalar_t> {
-  __device__ curve_config::scalar_t* getPointer()
-  {
-    extern __shared__ curve_config::scalar_t s_scalar_[];
-    return s_scalar_;
-  }
-};
-
-template <>
-struct SharedMemory<curve_config::projective_t> {
-  __device__ curve_config::projective_t* getPointer()
-  {
-    extern __shared__ curve_config::projective_t s_projective_[];
-    return s_projective_;
-  }
-};
-
 #endif //_SHAREDMEM_H_
 
 // Leave this at the end of the file

icicle/include/hash/keccak/keccak.cuh

@@ -3,8 +3,8 @@
 #define KECCAK_H
 
 #include <cstdint>
-#include "utils/device_context.cuh"
-#include "utils/error_handler.cuh"
+#include "gpu-utils/device_context.cuh"
+#include "gpu-utils/error_handler.cuh"
 
 namespace keccak {
   /**

icicle/include/msm/msm.cuh

@@ -4,12 +4,11 @@
 
 #include <cuda_runtime.h>
 
-#include "curves/curve_config.cuh"
-#include "primitives/affine.cuh"
-#include "primitives/field.cuh"
-#include "primitives/projective.cuh"
-#include "utils/device_context.cuh"
-#include "utils/error_handler.cuh"
+#include "curves/affine.cuh"
+#include "curves/projective.cuh"
+#include "fields/field.cuh"
+#include "gpu-utils/device_context.cuh"
+#include "gpu-utils/error_handler.cuh"
 
 /**
  * @namespace msm
@@ -87,7 +86,7 @@ namespace msm {
    * @return Default value of [MSMConfig](@ref MSMConfig).
    */
   template <typename A>
-  MSMConfig DefaultMSMConfig();
+  MSMConfig DefaultMSMConfig(const device_context::DeviceContext& ctx = device_context::get_default_device_context());
 
   /**
    * A function that computes MSM: \f$ MSM(s_i, P_i) = \sum_{i=1}^N s_i \cdot P_i \f$.

icicle/include/ntt/ntt.cuh

@@ -4,10 +4,9 @@
 
 #include <cuda_runtime.h>
 
-#include "curves/curve_config.cuh"
-#include "utils/device_context.cuh"
-#include "utils/error_handler.cuh"
-#include "utils/sharedmem.cuh"
+#include "gpu-utils/device_context.cuh"
+#include "gpu-utils/error_handler.cuh"
+#include "gpu-utils/sharedmem.cuh"
 #include "utils/utils_kernels.cuh"
 #include "utils/utils.h"
 
@@ -40,6 +39,31 @@ namespace ntt {
   template <typename S>
   cudaError_t InitDomain(S primitive_root, device_context::DeviceContext& ctx, bool fast_twiddles_mode = false);
 
+  /**
+   * Releases and deallocates resources associated with the domain initialized for performing NTTs.
+   * This function should be called to clean up resources once they are no longer needed.
+   * It's important to note that after calling this function, any operation that relies on the released domain will
+   * fail unless InitDomain is called again to reinitialize the resources. Therefore, ensure that ReleaseDomain is
+   * only called when the operations requiring the NTT domain are completely finished and the domain is no longer
+   * needed.
+   * Also note that it is releasing the domain associated to the specific device.
+   * @param ctx Details related to the device context such as its id and stream id.
+   * @return `cudaSuccess` if the resource release was successful, indicating that the domain and its associated
+   * resources have been properly deallocated. Returns an error code otherwise, indicating failure to release
+   * the resources. The error code can be used to diagnose the problem.
+   * */
+  template <typename S>
+  cudaError_t ReleaseDomain(device_context::DeviceContext& ctx);
+
+  /* Returns the basic root of unity Wn corresponding to the basic root used to initialize the domain.
+   * Useful when computing NTT on cosets. In that case we must use the root W_2n that is between W_n and W_n+1.
+   * @param logn log size of the required root.
+   * @param ctx Details related to the device such as its id and stream id.
+   * @return Wn root of unity corresponding to logn and the basic root used for initDomain(root)
+   */
+  template <typename S>
+  S GetRootOfUnity(uint64_t logn, device_context::DeviceContext& ctx);
+
   /**
    * @enum NTTDir
    * Whether to perform normal forward NTT, or inverse NTT (iNTT). Mathematically, forward NTT computes polynomial
@@ -114,7 +138,8 @@ namespace ntt {
    * @return Default value of [NTTConfig](@ref NTTConfig).
    */
   template <typename S>
-  NTTConfig<S> DefaultNTTConfig();
+  NTTConfig<S>
+  DefaultNTTConfig(const device_context::DeviceContext& ctx = device_context::get_default_device_context());
 
   /**
    * A function that computes NTT or iNTT in-place. It's necessary to call [InitDomain](@ref InitDomain) with an

icicle/include/ntt/ntt_impl.cuh

@@ -3,9 +3,9 @@
 #define _NTT_IMPL_H
 
 #include <stdint.h>
-#include "appUtils/ntt/ntt.cuh" // for enum Ordering
+#include "ntt/ntt.cuh" // for enum Ordering
 
-namespace ntt {
+namespace mxntt {
 
   template <typename S>
   cudaError_t generate_external_twiddles_generic(
@@ -38,10 +38,10 @@ namespace ntt {
     bool columns_batch,
     bool is_inverse,
     bool fast_tw,
-    Ordering ordering,
+    ntt::Ordering ordering,
     S* arbitrary_coset,
     int coset_gen_index,
     cudaStream_t cuda_stream);
 
-} // namespace ntt
+} // namespace mxntt
 #endif //_NTT_IMPL_H

icicle/include/polynomials/cuda_backend/polynomial_cuda_backend.cuh

@@ -0,0 +1,23 @@
+#pragma once
+
+#include "gpu-utils/device_context.cuh"
+#include "fields/field_config.cuh"
+#include "polynomials/polynomials.h"
+
+using device_context::DeviceContext;
+
+namespace polynomials {
+  template <typename C = scalar_t, typename D = C, typename I = C>
+  class CUDAPolynomialFactory : public AbstractPolynomialFactory<C, D, I>
+  {
+    std::vector<DeviceContext> m_device_contexts; // device-id --> device context
+    std::vector<cudaStream_t> m_device_streams;   // device-id --> device stream. Storing the streams here as workaround
+                                                  // since DeviceContext has a reference to a stream.
+
+  public:
+    CUDAPolynomialFactory();
+    ~CUDAPolynomialFactory();
+    std::shared_ptr<IPolynomialContext<C, D, I>> create_context() override;
+    std::shared_ptr<IPolynomialBackend<C, D, I>> create_backend() override;
+  };
+} // namespace polynomials

icicle/include/polynomials/polynomial_abstract_factory.h

@@ -0,0 +1,49 @@
+#pragma once
+
+#include "polynomial_context.h"
+#include "polynomial_backend.h"
+#include <memory> // For std::shared_ptr
+
+namespace polynomials {
+
+  /**
+   * @brief Abstract factory for creating polynomial contexts and backends.
+   *
+   * The `AbstractPolynomialFactory` serves as an interface for factories capable of creating
+   * instances of `IPolynomialContext` and `IPolynomialBackend`. This design allows for the
+   * decoupling of object creation from their usage, facilitating the implementation of various
+   * computational strategies (e.g., GPU, ZPU) without altering client code. Each concrete factory
+   * is expected to provide tailored implementations of polynomial contexts and backends that
+   * are optimized for specific computational environments.
+   *
+   * @tparam C Type of the coefficients.
+   * @tparam D Domain type, representing the input space of the polynomial.
+   * @tparam I Image type, representing the output space of the polynomial.
+   */
+  template <typename C, typename D, typename I>
+  class AbstractPolynomialFactory
+  {
+  public:
+    /**
+     * @brief Creates and returns a shared pointer to an `IPolynomialContext` instance.
+     *
+     * @return std::shared_ptr<IPolynomialContext<C, D, I>> A shared pointer to the created
+     *         polynomial context instance.
+     */
+    virtual std::shared_ptr<IPolynomialContext<C, D, I>> create_context() = 0;
+
+    /**
+     * @brief Creates and returns a shared pointer to an `IPolynomialBackend` instance.
+     *
+     * @return std::shared_ptr<IPolynomialBackend<C, D, I>> A shared pointer to the created
+     *         polynomial backend instance.
+     */
+    virtual std::shared_ptr<IPolynomialBackend<C, D, I>> create_backend() = 0;
+
+    /**
+     * @brief Virtual destructor for the `AbstractPolynomialFactory`.
+     */
+    virtual ~AbstractPolynomialFactory() = default;
+  };
+
+} // namespace polynomials

icicle/include/polynomials/polynomial_backend.h

@@ -0,0 +1,72 @@
+#pragma once
+
+#include <cstdint> // for uint64_t, int64_t
+
+namespace polynomials {
+
+  /**
+   * @brief Interface for the polynomial computational backend.
+   *
+   * The `IPolynomialBackend` interface defines the set of operations for polynomial arithmetic
+   * and manipulation that can be performed on a given computational device or platform (e.g., GPU, ZPU).
+   * This interface abstracts the computational logic, allowing for implementation-specific optimizations
+   * and hardware utilization. It interacts closely with `IPolynomialContext` to manage polynomial data
+   * states and perform computations.
+   *
+   * @tparam C Type of the coefficients.
+   * @tparam D Domain type, representing the input space of the polynomial.
+   * @tparam I Image type, representing the output space of the polynomial.
+   */
+  template <typename C, typename D, typename I>
+  class IPolynomialBackend
+  {
+  public:
+    IPolynomialBackend() = default;
+    virtual ~IPolynomialBackend() = default;
+
+    typedef std::shared_ptr<IPolynomialContext<C, D, I>> PolyContext;
+
+    // Initialization methods
+    virtual void from_coefficients(PolyContext p, uint64_t nof_coefficients, const C* coefficients = nullptr) = 0;
+    virtual void from_rou_evaluations(PolyContext p, uint64_t nof_evaluations, const I* evaluations = nullptr) = 0;
+    virtual void clone(PolyContext out, PolyContext in) = 0;
+
+    // Arithmetic operations
+    virtual void add(PolyContext& out, PolyContext op_a, PolyContext op_b) = 0;
+    virtual void subtract(PolyContext out, PolyContext op_a, PolyContext op_b) = 0;
+    virtual void multiply(PolyContext out, PolyContext op_a, PolyContext op_b) = 0;
+    virtual void multiply(PolyContext out, PolyContext p, D scalar) = 0; // scalar multiplication
+    virtual void divide(PolyContext Quotient_out, PolyContext Remainder_out, PolyContext op_a, PolyContext op_b) = 0;
+    virtual void quotient(PolyContext out, PolyContext op_a, PolyContext op_b) = 0;
+    virtual void remainder(PolyContext out, PolyContext op_a, PolyContext op_b) = 0;
+    virtual void divide_by_vanishing_polynomial(PolyContext out, PolyContext op_a, uint64_t vanishing_poly_degree) = 0;
+
+    // Operations specific to monomials
+    virtual void add_monomial_inplace(PolyContext& poly, C monomial_coeff, uint64_t monomial) = 0;
+    virtual void sub_monomial_inplace(PolyContext& poly, C monomial_coeff, uint64_t monomial) = 0;
+
+    // Utility methods
+    virtual void slice(PolyContext out, PolyContext in, uint64_t offset, uint64_t stride, uint64_t size) = 0;
+    virtual int64_t degree(PolyContext op) = 0;
+
+    // Method to access mutable storage within the context
+    void* get_context_storage_mutable(PolyContext ctxt) { return ctxt->get_storage_mutable(); }
+    const void* get_context_storage_immutable(PolyContext ctxt) { return ctxt->get_storage_immutable(); }
+
+    // Evaluation methods
+    virtual I evaluate(PolyContext op, const D& domain_x) = 0;
+    virtual void evaluate_on_domain(PolyContext op, const D* domain, uint64_t size, I* evaluations /*OUT*/) = 0;
+
+    // Methods to copy coefficients to host memory
+    virtual C copy_coefficient_to_host(PolyContext op, uint64_t coeff_idx) = 0;
+    virtual int64_t
+    copy_coefficients_to_host(PolyContext op, C* host_coeffs, int64_t start_idx = 0, int64_t end_idx = -1) = 0;
+
+    // Methods to get views of coefficients and evaluations, including device id
+    virtual std::tuple<IntegrityPointer<C>, uint64_t /*size*/, uint64_t /*device_id*/>
+    get_coefficients_view(PolyContext p) = 0;
+    virtual std::tuple<IntegrityPointer<I>, uint64_t /*size*/, uint64_t /*device_id*/>
+    get_rou_evaluations_view(PolyContext p, uint64_t nof_evaluations = 0, bool is_reversed = false) = 0;
+  };
+
+} // namespace polynomials

icicle/include/polynomials/polynomial_context.h

@@ -0,0 +1,93 @@
+#pragma once
+
+#include <utility>   // for std::pair
+#include <tuple>     // for std::tuple
+#include <iostream>  // for std::ostream
+#include <algorithm> // for std::max
+#include <cstdint>   // for uint64_t, etc.
+#include <memory>
+#include "utils/integrity_pointer.h"
+
+namespace polynomials {
+
+  template <typename Coeff, typename Domain, typename Image>
+  class IPolynomialBackend;
+
+  /**
+   * @brief Interface for polynomial context, encapsulating state, memory, and device context.
+   *
+   * This interface is designed to manage the state of polynomials including their coefficients and
+   * evaluations in both natural and reversed order. It supports operations for converting between
+   * these forms, allocating and releasing resources, and accessing the underlying data. The context
+   * abstracts over the specifics of memory and execution context, allowing polynomials to be managed
+   * in a way that is agnostic to the underlying hardware or software infrastructure.
+   *
+   * @tparam C Type of the coefficients.
+   * @tparam D Domain type, representing the input space of the polynomial.
+   * @tparam I Image type, representing the output space of the polynomial.
+   */
+  template <typename C, typename D, typename I>
+  class IPolynomialContext
+  {
+  public:
+    friend class IPolynomialBackend<C, D, I>;
+
+    // Enumerates the possible states of a polynomial context.
+    enum State { Invalid, Coefficients, EvaluationsOnRou_Natural, EvaluationsOnRou_Reversed };
+
+    // The size of the largest element among coefficients and evaluations.
+    static constexpr size_t ElementSize = std::max(sizeof(C), sizeof(I));
+
+    /**
+     * @brief Construct a new IPolynomialContext object.
+     */
+    IPolynomialContext() : m_id{s_id++} {}
+
+    /**
+     * @brief Virtual destructor for IPolynomialContext.
+     */
+    virtual ~IPolynomialContext() = default;
+
+    // Methods for initializing the context from coefficients or evaluations.
+    virtual void from_coefficients(uint64_t nof_coefficients, const C* coefficients = nullptr) = 0;
+    virtual void from_rou_evaluations(uint64_t nof_evaluations, const I* evaluations = nullptr) = 0;
+
+    // Method for cloning the context from another instance.
+    virtual void clone(IPolynomialContext& from) = 0;
+
+    // Methods for resource management.
+    virtual void allocate(uint64_t nof_elements, State init_state = State::Coefficients, bool memset_zeros = true) = 0;
+    virtual void release() = 0;
+
+    // Methods for transforming between coefficients and evaluations.
+    virtual void transform_to_coefficients(uint64_t nof_coefficients = 0) = 0;
+    virtual void transform_to_evaluations(uint64_t nof_evaluations = 0, bool is_reversed = false) = 0;
+
+    // Accessors for the state and number of elements.
+    virtual State get_state() const = 0;
+    virtual uint64_t get_nof_elements() const = 0;
+
+    // Methods to get direct access to coefficients and evaluations.
+    virtual std::pair<const C*, uint64_t> get_coefficients() = 0;
+    virtual std::pair<const I*, uint64_t> get_rou_evaluations() = 0;
+
+    // Methods to get views of coefficients and evaluations, including device id.
+    virtual std::tuple<IntegrityPointer<C>, uint64_t /*size*/, uint64_t /*device_id*/> get_coefficients_view() = 0;
+    virtual std::tuple<IntegrityPointer<I>, uint64_t /*size*/, uint64_t /*device_id*/>
+    get_rou_evaluations_view(uint64_t nof_evaluations = 0, bool is_reversed = false) = 0;
+
+    // Method for printing the context state to an output stream.
+    virtual void print(std::ostream& os) = 0;
+
+  protected:
+    // Provides mutable access to the underlying storage for backend computations.
+    virtual void* get_storage_mutable() = 0;
+    virtual const void* get_storage_immutable() = 0;
+
+    // Static and instance variables for debug id management.
+    static inline uint64_t s_id = 0; // Global id counter.
+
+  public:
+    const uint64_t m_id;
+  };
+} // namespace polynomials

icicle/include/polynomials/polynomials.h

@@ -0,0 +1,133 @@
+#pragma once
+
+#include <iostream>
+#include <memory>
+#include "utils/integrity_pointer.h"
+#include "fields/field_config.cuh"
+
+#include "polynomial_context.h"
+#include "polynomial_backend.h"
+#include "polynomial_abstract_factory.h"
+
+using namespace field_config;
+
+namespace polynomials {
+
+  /**
+   * @brief Represents a polynomial and provides operations for polynomial arithmetic, evaluation, and manipulation.
+   *
+   * This class models a polynomial with coefficients of type `Coeff`, defined over a domain `Domain` and producing
+   * outputs of type `Image`. It supports a range of operations including basic arithmetic (addition, subtraction,
+   * multiplication, division), evaluation at points or over domains, and manipulation (slicing, adding monomials).
+   * The implementation abstracts over the specifics of computation and storage through the use of an abstract factory,
+   * contexts, and backends, allowing for efficient execution across various computational environments.
+   *
+   * @tparam Coeff Type of the coefficients of the polynomial.
+   * @tparam Domain Type representing the input space of the polynomial (defaults to `Coeff`).
+   * @tparam Image Type representing the output space of the polynomial (defaults to `Coeff`).
+   */
+  template <typename Coeff, typename Domain = Coeff, typename Image = Coeff>
+  class Polynomial
+  {
+  public:
+    // Initialization (coefficients/evaluations can reside on host or device)
+    static Polynomial from_coefficients(const Coeff* coefficients, uint64_t nof_coefficients);
+    static Polynomial from_rou_evaluations(const Image* evaluations, uint64_t nof_evaluations);
+
+    // Clone the polynomial
+    Polynomial clone() const;
+
+    // Arithmetic ops
+    Polynomial operator+(const Polynomial& rhs) const;
+    Polynomial& operator+=(const Polynomial& rhs);
+
+    Polynomial operator-(const Polynomial& rhs) const;
+
+    Polynomial operator*(const Polynomial& rhs) const;
+    Polynomial operator*(const Domain& scalar) const; // scalar multiplication
+    template <typename C, typename D, typename I>
+    friend Polynomial<C, D, I> operator*(const D& scalar, const Polynomial<C, D, I>& rhs);
+
+    std::pair<Polynomial, Polynomial> divide(const Polynomial& rhs) const; //  returns (Q(x), R(x))
+    Polynomial operator/(const Polynomial& rhs) const; // returns Quotient Q(x) for A(x) = Q(x)B(x) + R(x)
+    Polynomial operator%(const Polynomial& rhs) const; // returns Remainder R(x) for A(x) = Q(x)B(x) + R(x)
+    Polynomial divide_by_vanishing_polynomial(uint64_t degree) const;
+
+    // arithmetic ops with monomial
+    Polynomial& add_monomial_inplace(Coeff monomial_coeff, uint64_t monomial = 0);
+    Polynomial& sub_monomial_inplace(Coeff monomial_coeff, uint64_t monomial = 0);
+
+    // Slicing and selecting even or odd components.
+    Polynomial slice(uint64_t offset, uint64_t stride, uint64_t size = 0 /*0 means take all elements*/);
+    Polynomial even();
+    Polynomial odd();
+
+    // Note: Following ops cannot be traced. Calling them invokes polynomial evaluation
+
+    // Evaluation methods
+    Image operator()(const Domain& x) const;
+    Image evaluate(const Domain& x) const;
+    void evaluate_on_domain(Domain* domain, uint64_t size, Image* evals /*OUT*/) const; // caller allocates memory
+
+    // Method to obtain the degree of the polynomial
+    int64_t degree();
+
+    // Methods for copying coefficients to host memory.
+    Coeff copy_coefficient_to_host(uint64_t idx) const; // single coefficient
+    // caller is allocating output memory. If coeff==nullptr, returning nof_coeff only
+    int64_t copy_coefficients_to_host(Coeff* host_coeffs = nullptr, int64_t start_idx = 0, int64_t end_idx = -1) const;
+
+    // Methods for obtaining a view of the coefficients or evaluations
+    std::tuple<IntegrityPointer<Coeff>, uint64_t /*size*/, uint64_t /*device_id*/> get_coefficients_view();
+    std::tuple<IntegrityPointer<Image>, uint64_t /*size*/, uint64_t /*device_id*/>
+    get_rou_evaluations_view(uint64_t nof_evaluations = 0, bool is_reversed = false);
+
+    // Overload stream insertion operator for printing.
+    friend std::ostream& operator<<(std::ostream& os, Polynomial& poly)
+    {
+      poly.m_context->print(os);
+      return os;
+    }
+
+    // Static method to initialize the polynomial class with a factory for context and backend creation.
+    static void initialize(std::shared_ptr<AbstractPolynomialFactory<Coeff, Domain, Image>> factory)
+    {
+      std::atexit(cleanup);
+      s_factory = factory;
+    }
+
+    // Cleanup method for releasing factory resources.
+    static void cleanup() { s_factory = nullptr; }
+
+  private:
+    // The context of the polynomial, encapsulating its state.
+    std::shared_ptr<IPolynomialContext<Coeff, Domain, Image>> m_context = nullptr;
+    // The computational backend for the polynomial operations.
+    std::shared_ptr<IPolynomialBackend<Coeff, Domain, Image>> m_backend = nullptr;
+
+    // Factory for constructing the context and backend instances.
+    static inline std::shared_ptr<AbstractPolynomialFactory<Coeff, Domain, Image>> s_factory = nullptr;
+
+  public:
+    Polynomial();
+    ~Polynomial() = default;
+
+    // Ensures polynomials can be moved but not copied, to manage resources efficiently.
+    Polynomial(Polynomial&&) = default;
+    Polynomial& operator=(Polynomial&&) = default;
+    Polynomial(const Polynomial&) = delete;
+    Polynomial& operator=(const Polynomial&) = delete;
+
+    std::shared_ptr<IPolynomialContext<Coeff, Domain, Image>> get_context() { return m_context; }
+  };
+
+  // explicit instantiation
+
+  // Friend operator to allow multiplication with a scalar from the left-hand side
+  template <typename C = scalar_t, typename D = C, typename I = C>
+  Polynomial<C, D, I> operator*(const D& scalar, const Polynomial<C, D, I>& rhs);
+
+  // External template instantiation to ensure the template is compiled for specific types.
+  extern template class Polynomial<scalar_t>;
+
+} // namespace polynomials

icicle/include/polynomials/polynomials_c_api.h

@@ -0,0 +1,247 @@
+#pragma once
+
+#include "polynomials.h"
+#include "fields/field_config.cuh"
+#include "utils/utils.h"
+#include "utils/integrity_pointer.h"
+
+namespace polynomials {
+  extern "C" {
+
+  // Defines a polynomial instance based on the scalar type from the FIELD configuration.
+  typedef Polynomial<scalar_t> PolynomialInst;
+
+  // Constructs a polynomial from a set of coefficients.
+  // coeffs: Array of coefficients.
+  // size: Number of coefficients in the array.
+  // Returns a pointer to the newly created polynomial instance.
+  PolynomialInst* CONCAT_EXPAND(FIELD, polynomial_create_from_coefficients)(scalar_t* coeffs, size_t size)
+  {
+    auto result = new PolynomialInst(PolynomialInst::from_coefficients(coeffs, size));
+    return result;
+  }
+
+  // Constructs a polynomial from evaluations at the roots of unity.
+  // evals: Array of evaluations.
+  // size: Number of evaluations in the array.
+  // Returns a pointer to the newly created polynomial instance.
+  PolynomialInst* CONCAT_EXPAND(FIELD, polynomial_create_from_rou_evaluations)(scalar_t* evals, size_t size)
+  {
+    auto result = new PolynomialInst(PolynomialInst::from_rou_evaluations(evals, size));
+    return result;
+  }
+
+  // Clones an existing polynomial instance.
+  // p: Pointer to the polynomial instance to clone.
+  // Returns a pointer to the cloned polynomial instance.
+  PolynomialInst* CONCAT_EXPAND(FIELD, polynomial_clone)(const PolynomialInst* p)
+  {
+    auto result = new PolynomialInst(p->clone());
+    return result;
+  }
+
+  // Deletes a polynomial instance, freeing its memory.
+  // instance: Pointer to the polynomial instance to delete.
+  void CONCAT_EXPAND(FIELD, polynomial_delete)(PolynomialInst* instance) { delete instance; }
+
+  // Adds two polynomials.
+  // a, b: Pointers to the polynomial instances to add.
+  // Returns a pointer to the resulting polynomial instance.
+  PolynomialInst* CONCAT_EXPAND(FIELD, polynomial_add)(const PolynomialInst* a, const PolynomialInst* b)
+  {
+    auto result = new PolynomialInst(std::move(*a + *b));
+    return result;
+  }
+
+  // Adds a polynomial to another in place.
+  // a: Pointer to the polynomial to add to.
+  // b: Pointer to the polynomial to add.
+  void CONCAT_EXPAND(FIELD, polynomial_add_inplace)(PolynomialInst* a, const PolynomialInst* b) { *a += *b; }
+
+  // Subtracts one polynomial from another.
+  // a, b: Pointers to the polynomial instances (minuend and subtrahend, respectively).
+  // Returns a pointer to the resulting polynomial instance.
+
+  PolynomialInst* CONCAT_EXPAND(FIELD, polynomial_subtract)(const PolynomialInst* a, const PolynomialInst* b)
+  {
+    auto result = new PolynomialInst(std::move(*a - *b));
+    return result;
+  }
+
+  // Multiplies two polynomials.
+  // a, b: Pointers to the polynomial instances to multiply.
+  // Returns a pointer to the resulting polynomial instance.
+  PolynomialInst* CONCAT_EXPAND(FIELD, polynomial_multiply)(const PolynomialInst* a, const PolynomialInst* b)
+  {
+    auto result = new PolynomialInst(std::move(*a * *b));
+    return result;
+  }
+
+  // Multiplies a polynomial by a scalar coefficient.
+  // a: Pointer to the polynomial instance.
+  // coeff: Scalar coefficient to multiply by.
+  // Returns a pointer to the resulting polynomial instance.
+  PolynomialInst* CONCAT_EXPAND(FIELD, polynomial_multiply_by_coeff)(const PolynomialInst* a, const scalar_t* coeff)
+  {
+    auto result = new PolynomialInst(std::move(*a * *coeff));
+    return result;
+  }
+
+  // Divides one polynomial by another, returning both quotient and remainder.
+  // a, b: Pointers to the polynomial instances (dividend and divisor, respectively).
+  // q: Output parameter for the quotient.
+  // r: Output parameter for the remainder.
+  void CONCAT_EXPAND(FIELD, polynomial_division)(
+    const PolynomialInst* a, const PolynomialInst* b, PolynomialInst** q /*OUT*/, PolynomialInst** r /*OUT*/)
+  {
+    auto [_q, _r] = a->divide(*b);
+    *q = new PolynomialInst(std::move(_q));
+    *r = new PolynomialInst(std::move(_r));
+  }
+
+  // Calculates the quotient of dividing one polynomial by another.
+  // a, b: Pointers to the polynomial instances (dividend and divisor, respectively).
+  // Returns a pointer to the resulting quotient polynomial instance.
+  PolynomialInst* CONCAT_EXPAND(FIELD, polynomial_quotient)(const PolynomialInst* a, const PolynomialInst* b)
+  {
+    auto result = new PolynomialInst(std::move(*a / *b));
+    return result;
+  }
+
+  // Calculates the remainder of dividing one polynomial by another.
+  // a, b: Pointers to the polynomial instances (dividend and divisor, respectively).
+  // Returns a pointer to the resulting remainder polynomial instance.
+
+  PolynomialInst* CONCAT_EXPAND(FIELD, polynomial_remainder)(const PolynomialInst* a, const PolynomialInst* b)
+  {
+    auto result = new PolynomialInst(std::move(*a % *b));
+    return result;
+  }
+
+  // Divides a polynomial by a vanishing polynomial of a given degree, over rou domain.
+  // p: Pointer to the polynomial instance.
+  // vanishing_poly_degree: Degree of the vanishing polynomial.
+  // Returns a pointer to the resulting polynomial instance.
+  PolynomialInst*
+  CONCAT_EXPAND(FIELD, polynomial_divide_by_vanishing)(const PolynomialInst* p, uint64_t vanishing_poly_degree)
+  {
+    auto result = new PolynomialInst(std::move(p->divide_by_vanishing_polynomial(vanishing_poly_degree)));
+    return result;
+  }
+
+  // Adds a monomial to a polynomial in place.
+  // p: Pointer to the polynomial instance.
+  // monomial_coeff: Coefficient of the monomial to add.
+  // monomial: Degree of the monomial to add.
+  void CONCAT_EXPAND(FIELD, polynomial_add_monomial_inplace)(
+    PolynomialInst* p, const scalar_t* monomial_coeff, uint64_t monomial)
+  {
+    p->add_monomial_inplace(*monomial_coeff, monomial);
+  }
+
+  // Subtracts a monomial from a polynomial in place.
+  // p: Pointer to the polynomial instance.
+  // monomial_coeff: Coefficient of the monomial to subtract.
+  // monomial: Degree of the monomial to subtract.
+  void CONCAT_EXPAND(FIELD, polynomial_sub_monomial_inplace)(
+    PolynomialInst* p, const scalar_t* monomial_coeff, uint64_t monomial)
+  {
+    p->sub_monomial_inplace(*monomial_coeff, monomial);
+  }
+
+  // Evaluates a polynomial at a given point.
+  // p: Pointer to the polynomial instance.
+  // x: Point at which to evaluate the polynomial.
+  // Returns the evaluation result.
+  scalar_t CONCAT_EXPAND(FIELD, polynomial_evaluate)(const PolynomialInst* p, const scalar_t& x)
+  {
+    return p->evaluate(x);
+  }
+
+  // Evaluates a polynomial on a domain of points.
+  // p: Pointer to the polynomial instance.
+  // domain: Array of points constituting the domain.
+  // domain_size: Number of points in the domain.
+  // evals: Output array for the evaluations.
+  void CONCAT_EXPAND(FIELD, polynomial_evaluate_on_domain)(
+    const PolynomialInst* p, scalar_t* domain, uint64_t domain_size, scalar_t* evals /*OUT*/)
+  {
+    return p->evaluate_on_domain(domain, domain_size, evals);
+  }
+
+  // Returns the degree of a polynomial.
+  // p: Pointer to the polynomial instance.
+  // Returns the degree of the polynomial.
+  int64_t CONCAT_EXPAND(FIELD, polynomial_degree)(PolynomialInst* p) { return p->degree(); }
+
+  // Copies a single coefficient of a polynomial to host memory.
+  // p: Pointer to the polynomial instance.
+  // idx: Index of the coefficient to copy.
+  // Returns the coefficient value.
+  scalar_t CONCAT_EXPAND(FIELD, polynomial_copy_single_coeff_to_host)(PolynomialInst* p, uint64_t idx)
+  {
+    return p->copy_coefficient_to_host(idx);
+  }
+
+  // Copies a range of polynomial coefficients to host memory.
+  // p: Pointer to the polynomial instance.
+  // host_memory: Array to copy the coefficients into. If NULL, not copying.
+  // start_idx: Start index of the range to copy.
+  // end_idx: End index of the range to copy.
+  // Returns the number of coefficients copied. if host_memory is NULL, returns number of coefficients.
+  int64_t CONCAT_EXPAND(FIELD, polynomial_coeffs_to_host)(
+    PolynomialInst* p, scalar_t* host_memory, uint64_t start_idx, uint64_t end_idx)
+  {
+    return p->copy_coefficients_to_host(host_memory, start_idx, end_idx);
+  }
+
+  // Retrieves a device-memory view of the polynomial coefficients.
+  // p: Pointer to the polynomial instance.
+  // size: Output parameter for the size of the view.
+  // device_id: Output parameter for the device ID.
+  // Returns a pointer to an integrity pointer encapsulating the coefficients view.
+  IntegrityPointer<scalar_t>* CONCAT_EXPAND(FIELD, polynomial_get_coeff_view)(
+    PolynomialInst* p, uint64_t* size /*OUT*/, uint64_t* device_id /*OUT*/)
+  {
+    auto [coeffs, _size, _device_id] = p->get_coefficients_view();
+    *size = _size;
+    *device_id = _device_id;
+    return new IntegrityPointer<scalar_t>(std::move(coeffs));
+  }
+
+  // Retrieves a device-memory view of the polynomial's evaluations on the roots of unity.
+  // p: Pointer to the polynomial instance.
+  // nof_evals: Number of evaluations.
+  // is_reversed: Whether the evaluations are in reversed order.
+  // size: Output parameter for the size of the view.
+  // device_id: Output parameter for the device ID.
+  // Returns a pointer to an integrity pointer encapsulating the evaluations view.
+  IntegrityPointer<scalar_t>* CONCAT_EXPAND(FIELD, polynomial_get_rou_evaluations_view)(
+    PolynomialInst* p, uint64_t nof_evals, bool is_reversed, uint64_t* size /*OUT*/, uint64_t* device_id /*OUT*/)
+  {
+    auto [rou_evals, _size, _device_id] = p->get_rou_evaluations_view(nof_evals, is_reversed);
+    *size = _size;
+    *device_id = _device_id;
+    return new IntegrityPointer<scalar_t>(std::move(rou_evals));
+  }
+
+  // Reads the pointer from an integrity pointer.
+  // p: Pointer to the integrity pointer.
+  // Returns the raw pointer if still valid, otherwise NULL.
+  const scalar_t* CONCAT_EXPAND(FIELD, polynomial_intergrity_ptr_get)(IntegrityPointer<scalar_t>* p)
+  {
+    return p->get();
+  }
+
+  // Checks if an integrity pointer is still valid.
+  // p: Pointer to the integrity pointer.
+  // Returns true if the pointer is valid, false otherwise.
+  bool CONCAT_EXPAND(FIELD, polynomial_intergrity_ptr_is_valid)(IntegrityPointer<scalar_t>* p) { return p->isValid(); }
+
+  // Destroys an integrity pointer, freeing its resources.
+  // p: Pointer to the integrity pointer to destroy.
+  void CONCAT_EXPAND(FIELD, polynomial_intergrity_ptr_destroy)(IntegrityPointer<scalar_t>* p) { delete p; }
+
+  } // extern "C"
+
+} // namespace polynomials

icicle/include/poseidon/poseidon.cuh

@@ -4,9 +4,8 @@
 
 #include <cstdint>
 #include <stdexcept>
-#include "utils/device_context.cuh"
-#include "curves/curve_config.cuh"
-#include "utils/error_handler.cuh"
+#include "gpu-utils/device_context.cuh"
+#include "gpu-utils/error_handler.cuh"
 #include "utils/utils.h"
 
 /**

icicle/include/poseidon/tree/merkle.cuh

@@ -2,10 +2,10 @@
 #ifndef MERKLE_H
 #define MERKLE_H
 
-#include "utils/device_context.cuh"
-#include "utils/error_handler.cuh"
+#include "gpu-utils/device_context.cuh"
+#include "gpu-utils/error_handler.cuh"
 #include "utils/utils.h"
-#include "appUtils/poseidon/poseidon.cuh"
+#include "poseidon/poseidon.cuh"
 
 #include <iostream>
 #include <math.h>

icicle/include/utils/integrity_pointer.h

@@ -0,0 +1,102 @@
+#pragma once
+
+#include <memory>
+#include <iostream>
+#include <stdexcept>
+
+/**
+ * @brief A template class that wraps a raw pointer with additional checks for data integrity.
+ *
+ * IntegrityPointer is designed to wrap a raw pointer and associate it with a validation
+ * mechanism based on a counter. This counter is monitored via a std::weak_ptr, allowing
+ * the IntegrityPointer to check if the data it points to has potentially been invalidated.
+ * It is intended for scenarios where there's a need to ensure the integrity of the pointed-to
+ * data throughout the lifetime of the pointer, particularly useful in complex systems where
+ * data validity can change over time due to external factors.
+ *
+ * Usage involves providing the raw pointer to be wrapped, a std::weak_ptr to a counter, and
+ * the expected value of that counter. The IntegrityPointer can then be used much like a normal
+ * pointer, with the addition of integrity checks before access.
+ *
+ * @tparam T The type of the pointed-to object.
+ */
+
+template <typename T>
+class IntegrityPointer
+{
+public:
+  /**
+   * Constructs an IntegrityPointer wrapping a raw pointer with a validity check based on a counter.
+   *
+   * @param ptr A raw pointer to the data of type T.
+   * @param counterWeakPtr A std::weak_ptr to an int counter, used for validation.
+   * @param expectedCounterValue The expected value of the counter for the pointer to be considered valid.
+   */
+  IntegrityPointer(const T* ptr, std::weak_ptr<int> counterWeakPtr, int expectedCounterValue)
+      : m_ptr(ptr), m_counterWeakPtr(counterWeakPtr), m_expectedCounterValue(expectedCounterValue)
+  {
+  }
+  IntegrityPointer(const IntegrityPointer& other) = default;
+  IntegrityPointer(IntegrityPointer&& other) = default;
+
+  /**
+   * Retrieves the raw pointer. Use with caution, as direct access bypasses validity checks.
+   * @return T* The raw pointer to the data.
+   */
+  const T* get() const { return isValid() ? m_ptr : nullptr; }
+
+  /**
+   * Dereferences the pointer. Throws std::runtime_error if the pointer is invalid.
+   * @return A reference to the data pointed to by the raw pointer.
+   */
+  const T& operator*() const
+  {
+    assertValid();
+    return *m_ptr;
+  }
+
+  /**
+   * Provides access to the member of the pointed-to object. Throws std::runtime_error if the pointer is invalid.
+   * @return T* The raw pointer to the data.
+   */
+  const T* operator->() const
+  {
+    assertValid();
+    return m_ptr;
+  }
+
+  /**
+   * Checks whether the pointer is still considered valid by comparing the current value of the counter
+   * to the expected value.
+   * @return true if the pointer is valid, false otherwise.
+   */
+  bool isValid() const
+  {
+    if (auto counterSharedPtr = m_counterWeakPtr.lock()) { return *counterSharedPtr == m_expectedCounterValue; }
+    return false;
+  }
+
+private:
+  const T* m_ptr;                      ///< The raw pointer to the data.
+  std::weak_ptr<int> m_counterWeakPtr; ///< A weak pointer to the counter used for validation.
+  const int m_expectedCounterValue;    ///< The expected value of the counter for the pointer to be valid.
+
+  /**
+   * Asserts the validity of the pointer. Throws std::runtime_error if the pointer is invalid.
+   */
+  void assertValid() const
+  {
+    if (!isValid()) {
+      logInvalidAccess();
+      throw std::runtime_error("Attempted to access invalidated IntegrityPointer.");
+    }
+  }
+
+  /**
+   * Logs an attempt to access an invalidated pointer.
+   */
+  static void logInvalidAccess()
+  {
+    std::cerr << "Warning: Attempted to access invalidated IntegrityPointer." << std::endl;
+  }
+};

icicle/include/utils/test_functions.cuh

@@ -0,0 +1,142 @@
+#pragma once
+
+template <class T1, class T2, int N_REP>
+__global__ void add_elements_kernel(const T1* x, const T2* y, T1* result, const unsigned count)
+{
+  const unsigned gid = blockIdx.x * blockDim.x + threadIdx.x;
+  if (gid >= count) return;
+  T1 res = x[gid];
+  T2 y_gid = y[gid];
+  for (int i = 0; i < N_REP; i++)
+    res = res + y_gid;
+  result[gid] = res;
+}
+
+template <class T1, class T2, int N_REP = 1>
+int vec_add(const T1* x, const T2* y, T1* result, const unsigned count)
+{
+  add_elements_kernel<T1, T2, N_REP><<<(count - 1) / 256 + 1, 256>>>(x, y, result, count);
+  int error = cudaGetLastError();
+  return (error || (N_REP > 1)) ? error : cudaDeviceSynchronize();
+}
+
+template <class T1, class T2>
+__global__ void sub_elements_kernel(const T1* x, const T2* y, T1* result, const unsigned count)
+{
+  const unsigned gid = blockIdx.x * blockDim.x + threadIdx.x;
+  if (gid >= count) return;
+  result[gid] = x[gid] - y[gid];
+}
+
+template <class T1, class T2>
+int vec_sub(const T1* x, const T2* y, T1* result, const unsigned count)
+{
+  sub_elements_kernel<T1, T2><<<(count - 1) / 256 + 1, 256>>>(x, y, result, count);
+  int error = cudaGetLastError();
+  return error ? error : cudaDeviceSynchronize();
+}
+
+template <class T>
+__global__ void neg_elements_kernel(const T* x, T* result, const unsigned count)
+{
+  const unsigned gid = blockIdx.x * blockDim.x + threadIdx.x;
+  if (gid >= count) return;
+  result[gid] = T::neg(x[gid]);
+}
+
+template <class T>
+int vec_neg(const T* x, T* result, const unsigned count)
+{
+  neg_elements_kernel<T><<<(count - 1) / 256 + 1, 256>>>(x, result, count);
+  int error = cudaGetLastError();
+  return error ? error : cudaDeviceSynchronize();
+}
+
+template <class F, class G, int N_REP>
+__global__ void mul_elements_kernel(const F* x, const G* y, G* result, const unsigned count)
+{
+  const unsigned gid = blockIdx.x * blockDim.x + threadIdx.x;
+  if (gid >= count) return;
+  F x_gid = x[gid];
+  G res = y[gid];
+  for (int i = 0; i < N_REP; i++)
+    res = res * x_gid;
+  result[gid] = res;
+}
+
+template <class F, class G, int N_REP = 1>
+int vec_mul(const F* x, const G* y, G* result, const unsigned count)
+{
+  mul_elements_kernel<F, G, N_REP><<<(count - 1) / 256 + 1, 256>>>(x, y, result, count);
+  int error = cudaGetLastError();
+  return (error || (N_REP > 1)) ? error : cudaDeviceSynchronize();
+}
+
+template <class F>
+__global__ void inv_field_elements_kernel(const F* x, F* result, const unsigned count)
+{
+  const unsigned gid = blockIdx.x * blockDim.x + threadIdx.x;
+  if (gid >= count) return;
+  result[gid] = F::inverse(x[gid]);
+}
+
+template <class F>
+int field_vec_inv(const F* x, F* result, const unsigned count)
+{
+  inv_field_elements_kernel<<<(count - 1) / 256 + 1, 256>>>(x, result, count);
+  int error = cudaGetLastError();
+  return error ? error : cudaDeviceSynchronize();
+}
+
+template <class F, int N_REP>
+__global__ void sqr_field_elements_kernel(const F* x, F* result, const unsigned count)
+{
+  const unsigned gid = blockIdx.x * blockDim.x + threadIdx.x;
+  if (gid >= count) return;
+  F x_gid = x[gid];
+  for (int i = 0; i < N_REP; i++)
+    x_gid = F::sqr(x_gid);
+  result[gid] = x_gid;
+}
+
+template <class F, int N_REP = 1>
+int field_vec_sqr(const F* x, F* result, const unsigned count)
+{
+  sqr_field_elements_kernel<F, N_REP><<<(count - 1) / 256 + 1, 256>>>(x, result, count);
+  int error = cudaGetLastError();
+  return (error || (N_REP > 1)) ? error : cudaDeviceSynchronize();
+}
+
+template <class P, class A>
+__global__ void to_affine_points_kernel(const P* x, A* result, const unsigned count)
+{
+  const unsigned gid = blockIdx.x * blockDim.x + threadIdx.x;
+  if (gid >= count) return;
+  result[gid] = P::to_affine(x[gid]);
+}
+
+template <class P, class A>
+int point_vec_to_affine(const P* x, A* result, const unsigned count)
+{
+  to_affine_points_kernel<P, A><<<(count - 1) / 256 + 1, 256>>>(x, result, count);
+  int error = cudaGetLastError();
+  return error ? error : cudaDeviceSynchronize();
+}
+
+template <class T>
+int device_populate_random(T* d_elements, unsigned n)
+{
+  T* h_elements = (T*)malloc(n * sizeof(T));
+  for (unsigned i = 0; i < n; i++)
+    h_elements[i] = T::rand_host();
+  return cudaMemcpy(d_elements, h_elements, sizeof(T) * n, cudaMemcpyHostToDevice);
+}
+
+template <class T>
+int device_set(T* d_elements, T el, unsigned n)
+{
+  T* h_elements = (T*)malloc(n * sizeof(T));
+  for (unsigned i = 0; i < n; i++)
+    h_elements[i] = el;
+  return cudaMemcpy(d_elements, h_elements, sizeof(T) * n, cudaMemcpyHostToDevice);
+}

icicle/include/vec_ops/vec_ops.cuh

@@ -2,7 +2,7 @@
 #ifndef LDE_H
 #define LDE_H
 
-#include "device_context.cuh"
+#include "gpu-utils/device_context.cuh"
 
 /**
  * @namespace vec_ops
@@ -24,9 +24,6 @@ namespace vec_ops {
 
     bool is_result_on_device; /**< If true, output is preserved on device, otherwise on host. Default value: false. */
 
-    bool is_result_montgomery_form; /**< True if `result` vector should be in Montgomery form and false otherwise.
-                                     *   Default value: false. */
-
     bool is_async; /**< Whether to run the vector operations asynchronously. If set to `true`, the function will be
                     *   non-blocking and you'd need to synchronize it explicitly by running
                     *   `cudaStreamSynchronize` or `cudaDeviceSynchronize`. If set to false, the
@@ -46,7 +43,6 @@ namespace vec_ops {
       false, // is_a_on_device
       false, // is_b_on_device
       false, // is_result_on_device
-      false, // is_result_montgomery_form
       false, // is_async
     };
     return config;
@@ -64,7 +60,7 @@ namespace vec_ops {
    * @return `cudaSuccess` if the execution was successful and an error code otherwise.
    */
   template <typename E, typename S>
-  cudaError_t Mul(S* vec_a, E* vec_b, int n, VecOpsConfig<E>& config, E* result);
+  cudaError_t Mul(const S* vec_a, const E* vec_b, int n, VecOpsConfig<E>& config, E* result);
 
   /**
    * A function that adds two vectors element-wise.
@@ -79,7 +75,7 @@ namespace vec_ops {
    * @return `cudaSuccess` if the execution was successful and an error code otherwise.
    */
   template <typename E>
-  cudaError_t Add(E* vec_a, E* vec_b, int n, VecOpsConfig<E>& config, E* result);
+  cudaError_t Add(const E* vec_a, const E* vec_b, int n, VecOpsConfig<E>& config, E* result);
 
   /**
    * A function that subtracts two vectors element-wise.
@@ -94,7 +90,31 @@ namespace vec_ops {
    * @return `cudaSuccess` if the execution was successful and an error code otherwise.
    */
   template <typename E>
-  cudaError_t Sub(E* vec_a, E* vec_b, int n, VecOpsConfig<E>& config, E* result);
+  cudaError_t Sub(const E* vec_a, const E* vec_b, int n, VecOpsConfig<E>& config, E* result);
+
+  /**
+   * Transposes an input matrix out-of-place inside GPU.
+   * for example: for ([a[0],a[1],a[2],a[3]], 2, 2) it returns
+   * [a[0],a[2],a[1],a[3]].
+   * @param mat_in array of some object of type E of size row_size * column_size.
+   * @param arr_out buffer of the same size as `mat_in` to write the transpose matrix into.
+   * @param row_size size of rows.
+   * @param column_size size of columns.
+   * @param ctx Device context.
+   * @param on_device Whether the input and output are on device.
+   * @param is_async Whether to run the vector operations asynchronously.
+   * @tparam E The type of elements `mat_in' and `mat_out`.
+   * @return `cudaSuccess` if the execution was successful and an error code otherwise.
+   */
+  template <typename E>
+  cudaError_t transpose_batch(
+    const E* mat_in,
+    E* mat_out,
+    uint32_t row_size,
+    uint32_t column_size,
+    device_context::DeviceContext& ctx,
+    bool on_device,
+    bool is_async);
 } // namespace vec_ops
 
 #endif

icicle/primitives/field.cu

@@ -1,10 +0,0 @@
-#include "curves/curve_config.cuh"
-#include "field.cuh"
-#include "utils/utils.h"
-
-using namespace curve_config;
-
-extern "C" void CONCAT_EXPAND(CURVE, GenerateScalars)(scalar_t* scalars, int size)
-{
-  scalar_t::RandHostMany(scalars, size);
-}

icicle/primitives/test_kernels.cuh

@@ -1,113 +0,0 @@
-#pragma once
-
-#include "curves/curve_config.cuh"
-
-using namespace curve_config;
-
-template <class T1, class T2>
-__global__ void add_elements_kernel(const T1* x, const T2* y, T1* result, const unsigned count)
-{
-  const unsigned gid = blockIdx.x * blockDim.x + threadIdx.x;
-  if (gid >= count) return;
-  result[gid] = x[gid] + y[gid];
-}
-
-template <class T1, class T2>
-int vec_add(const T1* x, const T2* y, T1* result, const unsigned count)
-{
-  add_elements_kernel<T1, T2><<<(count - 1) / 32 + 1, 32>>>(x, y, result, count);
-  int error = cudaGetLastError();
-  return error ? error : cudaDeviceSynchronize();
-}
-
-template <class T1, class T2>
-__global__ void sub_elements_kernel(const T1* x, const T2* y, T1* result, const unsigned count)
-{
-  const unsigned gid = blockIdx.x * blockDim.x + threadIdx.x;
-  if (gid >= count) return;
-  result[gid] = x[gid] - y[gid];
-}
-
-template <class T1, class T2>
-int vec_sub(const T1* x, const T2* y, T1* result, const unsigned count)
-{
-  sub_elements_kernel<T1, T2><<<(count - 1) / 32 + 1, 32>>>(x, y, result, count);
-  int error = cudaGetLastError();
-  return error ? error : cudaDeviceSynchronize();
-}
-
-template <class T>
-__global__ void neg_elements_kernel(const T* x, T* result, const unsigned count)
-{
-  const unsigned gid = blockIdx.x * blockDim.x + threadIdx.x;
-  if (gid >= count) return;
-  result[gid] = T::neg(x[gid]);
-}
-
-template <class T>
-int vec_neg(const T* x, T* result, const unsigned count)
-{
-  neg_elements_kernel<T><<<(count - 1) / 32 + 1, 32>>>(x, result, count);
-  int error = cudaGetLastError();
-  return error ? error : cudaDeviceSynchronize();
-}
-
-template <class F, class G>
-__global__ void mul_elements_kernel(const F* x, const G* y, G* result, const unsigned count)
-{
-  const unsigned gid = blockIdx.x * blockDim.x + threadIdx.x;
-  if (gid >= count) return;
-  result[gid] = x[gid] * y[gid];
-}
-
-template <class F, class G>
-int vec_mul(const F* x, const G* y, G* result, const unsigned count)
-{
-  mul_elements_kernel<F, G><<<(count - 1) / 32 + 1, 32>>>(x, y, result, count);
-  int error = cudaGetLastError();
-  return error ? error : cudaDeviceSynchronize();
-}
-
-__global__ void inv_field_elements_kernel(const scalar_t* x, scalar_t* result, const unsigned count)
-{
-  const unsigned gid = blockIdx.x * blockDim.x + threadIdx.x;
-  if (gid >= count) return;
-  result[gid] = scalar_t::inverse(x[gid]);
-}
-
-int field_vec_inv(const scalar_t* x, scalar_t* result, const unsigned count)
-{
-  inv_field_elements_kernel<<<(count - 1) / 32 + 1, 32>>>(x, result, count);
-  int error = cudaGetLastError();
-  return error ? error : cudaDeviceSynchronize();
-}
-
-__global__ void sqr_field_elements_kernel(const scalar_t* x, scalar_t* result, const unsigned count)
-{
-  const unsigned gid = blockIdx.x * blockDim.x + threadIdx.x;
-  if (gid >= count) return;
-  result[gid] = scalar_t::sqr(x[gid]);
-}
-
-int field_vec_sqr(const scalar_t* x, scalar_t* result, const unsigned count)
-{
-  sqr_field_elements_kernel<<<(count - 1) / 32 + 1, 32>>>(x, result, count);
-  int error = cudaGetLastError();
-  return error ? error : cudaDeviceSynchronize();
-}
-
-template <class P, class A>
-__global__ void to_affine_points_kernel(const P* x, A* result, const unsigned count)
-{
-  const unsigned gid = blockIdx.x * blockDim.x + threadIdx.x;
-  if (gid >= count) return;
-  result[gid] = P::to_affine(x[gid]);
-}
-
-template <class P, class A>
-int point_vec_to_affine(const P* x, A* result, const unsigned count)
-{
-  to_affine_points_kernel<P, A><<<(count - 1) / 32 + 1, 32>>>(x, result, count);
-  int error = cudaGetLastError();
-  return error ? error : cudaDeviceSynchronize();
-}

icicle/src/curves/CMakeLists.txt

@@ -0,0 +1,25 @@
+if (G2)
+  set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -DG2")
+endif ()
+
+set(TARGET icicle_curve)
+set(FIELD_TARGET icicle_field)
+
+set(SRC ${CMAKE_SOURCE_DIR}/src)
+
+set(CURVE_SOURCE ${SRC}/curves/extern.cu)
+list(APPEND CURVE_SOURCE ${SRC}/msm/extern.cu)
+if(G2)
+  list(APPEND CURVE_SOURCE ${SRC}/curves/extern_g2.cu)
+  list(APPEND CURVE_SOURCE ${SRC}/msm/extern_g2.cu)
+endif()
+if(ECNTT)
+  list(APPEND CURVE_SOURCE ${SRC}/ntt/extern_ecntt.cu)
+  list(APPEND CURVE_SOURCE ${SRC}/ntt/kernel_ntt.cu)
+endif()
+
+add_library(${TARGET} STATIC ${CURVE_SOURCE})
+target_include_directories(${TARGET} PUBLIC ${CMAKE_SOURCE_DIR}/include/)
+set_target_properties(${TARGET} PROPERTIES OUTPUT_NAME "ingo_curve_${CURVE}")
+target_compile_definitions(${TARGET} PUBLIC CURVE=${CURVE})
+target_link_libraries(${TARGET} PRIVATE ${FIELD_TARGET})

icicle/src/curves/extern.cu

@@ -0,0 +1,51 @@
+#include "curves/curve_config.cuh"
+
+using namespace curve_config;
+
+#include "gpu-utils/device_context.cuh"
+#include "utils/utils.h"
+#include "utils/mont.cuh"
+
+extern "C" bool CONCAT_EXPAND(CURVE, Eq)(projective_t* point1, projective_t* point2)
+{
+  return (*point1 == *point2) &&
+         !((point1->x == point_field_t::zero()) && (point1->y == point_field_t::zero()) &&
+           (point1->z == point_field_t::zero())) &&
+         !((point2->x == point_field_t::zero()) && (point2->y == point_field_t::zero()) &&
+           (point2->z == point_field_t::zero()));
+}
+
+extern "C" void CONCAT_EXPAND(CURVE, ToAffine)(projective_t* point, affine_t* point_out)
+{
+  *point_out = projective_t::to_affine(*point);
+}
+
+extern "C" void CONCAT_EXPAND(CURVE, GenerateProjectivePoints)(projective_t* points, int size)
+{
+  projective_t::RandHostMany(points, size);
+}
+
+extern "C" void CONCAT_EXPAND(CURVE, GenerateAffinePoints)(affine_t* points, int size)
+{
+  projective_t::RandHostManyAffine(points, size);
+}
+
+extern "C" cudaError_t CONCAT_EXPAND(CURVE, AffineConvertMontgomery)(
+  affine_t* d_inout, size_t n, bool is_into, device_context::DeviceContext& ctx)
+{
+  if (is_into) {
+    return mont::ToMontgomery(d_inout, n, ctx.stream, d_inout);
+  } else {
+    return mont::FromMontgomery(d_inout, n, ctx.stream, d_inout);
+  }
+}
+
+extern "C" cudaError_t CONCAT_EXPAND(CURVE, ProjectiveConvertMontgomery)(
+  projective_t* d_inout, size_t n, bool is_into, device_context::DeviceContext& ctx)
+{
+  if (is_into) {
+    return mont::ToMontgomery(d_inout, n, ctx.stream, d_inout);
+  } else {
+    return mont::FromMontgomery(d_inout, n, ctx.stream, d_inout);
+  }
+}

icicle/src/curves/extern_g2.cu

@@ -1,37 +1,10 @@
 #include "curves/curve_config.cuh"
-#include "projective.cuh"
-#include <cuda.h>
+
+using namespace curve_config;
+
+#include "gpu-utils/device_context.cuh"
 #include "utils/utils.h"
-
-using namespace curve_config;
-
-extern "C" bool CONCAT_EXPAND(CURVE, Eq)(projective_t* point1, projective_t* point2)
-{
-  return (*point1 == *point2) &&
-         !((point1->x == point_field_t::zero()) && (point1->y == point_field_t::zero()) &&
-           (point1->z == point_field_t::zero())) &&
-         !((point2->x == point_field_t::zero()) && (point2->y == point_field_t::zero()) &&
-           (point2->z == point_field_t::zero()));
-}
-
-extern "C" void CONCAT_EXPAND(CURVE, ToAffine)(projective_t* point, affine_t* point_out)
-{
-  *point_out = projective_t::to_affine(*point);
-}
-
-extern "C" void CONCAT_EXPAND(CURVE, GenerateProjectivePoints)(projective_t* points, int size)
-{
-  projective_t::RandHostMany(points, size);
-}
-
-extern "C" void CONCAT_EXPAND(CURVE, GenerateAffinePoints)(affine_t* points, int size)
-{
-  projective_t::RandHostManyAffine(points, size);
-}
-
-#if defined(G2_DEFINED)
-
-using namespace curve_config;
+#include "utils/mont.cuh"
 
 extern "C" bool CONCAT_EXPAND(CURVE, G2Eq)(g2_projective_t* point1, g2_projective_t* point2)
 {
@@ -57,4 +30,22 @@ extern "C" void CONCAT_EXPAND(CURVE, G2GenerateAffinePoints)(g2_affine_t* points
   g2_projective_t::RandHostManyAffine(points, size);
 }
 
-#endif
+extern "C" cudaError_t CONCAT_EXPAND(CURVE, G2AffineConvertMontgomery)(
+  g2_affine_t* d_inout, size_t n, bool is_into, device_context::DeviceContext& ctx)
+{
+  if (is_into) {
+    return mont::ToMontgomery(d_inout, n, ctx.stream, d_inout);
+  } else {
+    return mont::FromMontgomery(d_inout, n, ctx.stream, d_inout);
+  }
+}
+
+extern "C" cudaError_t CONCAT_EXPAND(CURVE, G2ProjectiveConvertMontgomery)(
+  g2_projective_t* d_inout, size_t n, bool is_into, device_context::DeviceContext& ctx)
+{
+  if (is_into) {
+    return mont::ToMontgomery(d_inout, n, ctx.stream, d_inout);
+  } else {
+    return mont::FromMontgomery(d_inout, n, ctx.stream, d_inout);
+  }
+}

icicle/src/fields/CMakeLists.txt

@@ -0,0 +1,39 @@
+if (EXT_FIELD)
+  set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -DEXT_FIELD")
+endif ()
+
+SET(SUPPORTED_FIELDS_WITHOUT_NTT grumpkin)
+
+set(TARGET icicle_field)
+
+set(SRC ${CMAKE_SOURCE_DIR}/src)
+
+set(FIELD_SOURCE ${SRC}/fields/extern.cu)
+list(APPEND FIELD_SOURCE ${SRC}/vec_ops/extern.cu)
+if(EXT_FIELD)
+  list(APPEND FIELD_SOURCE ${SRC}/fields/extern_extension.cu)
+  list(APPEND FIELD_SOURCE ${SRC}/ntt/extern_extension.cu)
+  list(APPEND FIELD_SOURCE ${SRC}/vec_ops/extern_extension.cu)
+endif()
+
+set(POLYNOMIAL_SOURCE_FILES 
+    ${SRC}/polynomials/polynomials.cu
+    ${SRC}/polynomials/cuda_backend/polynomial_cuda_backend.cu)
+
+list(APPEND FIELD_SOURCE ${POLYNOMIAL_SOURCE_FILES})
+
+# TODO: impl poseidon for small fields. note that it needs to be defined for the extension field!
+if (DEFINED CURVE)
+  list(APPEND FIELD_SOURCE ${SRC}/poseidon/poseidon.cu)
+  list(APPEND FIELD_SOURCE ${SRC}/poseidon/tree/merkle.cu)
+endif()
+
+if (NOT FIELD IN_LIST SUPPORTED_FIELDS_WITHOUT_NTT)
+  list(APPEND FIELD_SOURCE ${SRC}/ntt/extern.cu)
+  list(APPEND FIELD_SOURCE ${SRC}/ntt/kernel_ntt.cu)
+endif()
+
+add_library(${TARGET} STATIC ${FIELD_SOURCE})
+target_include_directories(${TARGET} PUBLIC ${CMAKE_SOURCE_DIR}/include/)
+set_target_properties(${TARGET} PROPERTIES OUTPUT_NAME "ingo_field_${FIELD}")
+target_compile_definitions(${TARGET} PUBLIC FIELD=${FIELD})

icicle/src/fields/extern.cu

@@ -0,0 +1,22 @@
+#include "fields/field_config.cuh"
+
+using namespace field_config;
+
+#include "utils/mont.cuh"
+#include "utils/utils.h"
+#include "gpu-utils/device_context.cuh"
+
+extern "C" void CONCAT_EXPAND(FIELD, GenerateScalars)(scalar_t* scalars, int size)
+{
+  scalar_t::RandHostMany(scalars, size);
+}
+
+extern "C" cudaError_t CONCAT_EXPAND(FIELD, ScalarConvertMontgomery)(
+  scalar_t* d_inout, size_t n, bool is_into, device_context::DeviceContext& ctx)
+{
+  if (is_into) {
+    return mont::ToMontgomery(d_inout, n, ctx.stream, d_inout);
+  } else {
+    return mont::FromMontgomery(d_inout, n, ctx.stream, d_inout);
+  }
+}

icicle/src/fields/extern_extension.cu

@@ -0,0 +1,22 @@
+#include "fields/field_config.cuh"
+
+using namespace field_config;
+
+#include "utils/mont.cuh"
+#include "utils/utils.h"
+#include "gpu-utils/device_context.cuh"
+
+extern "C" void CONCAT_EXPAND(FIELD, ExtensionGenerateScalars)(extension_t* scalars, int size)
+{
+  extension_t::RandHostMany(scalars, size);
+}
+
+extern "C" cudaError_t CONCAT_EXPAND(FIELD, ExtensionScalarConvertMontgomery)(
+  extension_t* d_inout, size_t n, bool is_into, device_context::DeviceContext& ctx)
+{
+  if (is_into) {
+    return mont::ToMontgomery(d_inout, n, ctx.stream, d_inout);
+  } else {
+    return mont::FromMontgomery(d_inout, n, ctx.stream, d_inout);
+  }
+}

icicle/src/hash/CMakeLists.txt

@@ -0,0 +1,5 @@
+set(TARGET icicle_hash)
+
+add_library(${TARGET} STATIC keccak/keccak.cu)
+target_include_directories(${TARGET} PUBLIC ${CMAKE_SOURCE_DIR}/include/)
+set_target_properties(${TARGET} PROPERTIES OUTPUT_NAME "ingo_hash")

icicle/src/hash/keccak/keccak.cu

@@ -1,4 +1,4 @@
-#include "keccak.cuh"
+#include "hash/keccak/keccak.cuh"
 
 namespace keccak {
 #define ROTL64(x, y) (((x) << (y)) | ((x) >> (64 - (y))))

icicle/src/msm/extern.cu

@@ -0,0 +1,43 @@
+#include "curves/curve_config.cuh"
+#include "fields/field_config.cuh"
+
+using namespace curve_config;
+using namespace field_config;
+
+#include "msm.cu"
+#include "utils/utils.h"
+
+namespace msm {
+  /**
+   * Extern "C" version of [PrecomputeMSMBases](@ref PrecomputeMSMBases) function with the following values of template
+   * parameters (where the curve is given by `-DCURVE` env variable during build):
+   *  - `A` is the [affine representation](@ref affine_t) of curve points;
+   * @return `cudaSuccess` if the execution was successful and an error code otherwise.
+   */
+  extern "C" cudaError_t CONCAT_EXPAND(CURVE, PrecomputeMSMBases)(
+    affine_t* bases,
+    int bases_size,
+    int precompute_factor,
+    int _c,
+    bool are_bases_on_device,
+    device_context::DeviceContext& ctx,
+    affine_t* output_bases)
+  {
+    return PrecomputeMSMBases<affine_t, projective_t>(
+      bases, bases_size, precompute_factor, _c, are_bases_on_device, ctx, output_bases);
+  }
+
+  /**
+   * Extern "C" version of [MSM](@ref MSM) function with the following values of template parameters
+   * (where the curve is given by `-DCURVE` env variable during build):
+   *  - `S` is the [scalar field](@ref scalar_t) of the curve;
+   *  - `A` is the [affine representation](@ref affine_t) of curve points;
+   *  - `P` is the [projective representation](@ref projective_t) of curve points.
+   * @return `cudaSuccess` if the execution was successful and an error code otherwise.
+   */
+  extern "C" cudaError_t CONCAT_EXPAND(CURVE, MSMCuda)(
+    const scalar_t* scalars, const affine_t* points, int msm_size, MSMConfig& config, projective_t* out)
+  {
+    return MSM<scalar_t, affine_t, projective_t>(scalars, points, msm_size, config, out);
+  }
+} // namespace msm

icicle/src/msm/extern_g2.cu

@@ -0,0 +1,43 @@
+#include "curves/curve_config.cuh"
+#include "fields/field_config.cuh"
+
+using namespace curve_config;
+using namespace field_config;
+
+#include "msm.cu"
+#include "utils/utils.h"
+
+namespace msm {
+  /**
+   * Extern "C" version of [PrecomputeMSMBases](@ref PrecomputeMSMBases) function with the following values of template
+   * parameters (where the curve is given by `-DCURVE` env variable during build):
+   *  - `A` is the [affine representation](@ref g2_affine_t) of G2 curve points;
+   * @return `cudaSuccess` if the execution was successful and an error code otherwise.
+   */
+  extern "C" cudaError_t CONCAT_EXPAND(CURVE, G2PrecomputeMSMBases)(
+    g2_affine_t* bases,
+    int bases_size,
+    int precompute_factor,
+    int _c,
+    bool are_bases_on_device,
+    device_context::DeviceContext& ctx,
+    g2_affine_t* output_bases)
+  {
+    return PrecomputeMSMBases<g2_affine_t, g2_projective_t>(
+      bases, bases_size, precompute_factor, _c, are_bases_on_device, ctx, output_bases);
+  }
+
+  /**
+   * Extern "C" version of [MSM](@ref MSM) function with the following values of template parameters
+   * (where the curve is given by `-DCURVE` env variable during build):
+   *  - `S` is the [scalar field](@ref scalar_t) of the curve;
+   *  - `A` is the [affine representation](@ref g2_affine_t) of G2 curve points;
+   *  - `P` is the [projective representation](@ref g2_projective_t) of G2 curve points.
+   * @return `cudaSuccess` if the execution was successful and an error code otherwise.
+   */
+  extern "C" cudaError_t CONCAT_EXPAND(CURVE, G2MSMCuda)(
+    const scalar_t* scalars, const g2_affine_t* points, int msm_size, MSMConfig& config, g2_projective_t* out)
+  {
+    return MSM<scalar_t, g2_affine_t, g2_projective_t>(scalars, points, msm_size, config, out);
+  }
+} // namespace msm