The current scheme used by reinstantiating conversion patterns in
`lib/Conversion/Utils/Dialects` for operations with blocks is to
create a new operation with empty blocks, to move the operations from
the old blocks and then to replace any references to block
arguments. However, such in-place updates of the types of block
arguments leave conversion patterns for operations nested in the
blocks without the ability to determine the original types of values
from before the update.
This change uses proper signature conversion for block arguments, such
that the original types of block arguments with converted types is
preserved, while the new types are made available through the dialect
conversion infrastructure via the respective adaptors.
Some of the TFHE to Concrete conversion patterns implicitly assume
that operands are ciphertexts and thus that the converted types have a
higher number of dimensions than the original types. However, for
non-ciphertext types, the number of dimensions before and after the
conversion must be the same.
This commit adds a check to the respective conversion patterns
triggering a simple type conversion that preserves the number of
dimensions for non-ciphertext types.
This introduces a new function `normalizeInductionVar()` to the static
loop utility code in `concretelang/Analysis/StaticLoops.h` with code
extracted for IV normalization from the batching code and changes the
batching code to make use of the factored function.
This adds support for the tiling of `linalg.generic` operations that
have only parallel iterators or only parallel iterators and a single
reduction dimension via the linalg tiling infrastructure (i.e.,
`mlir::linalg::tileToForallOpUsingTileSizes()` and
`mlir::linalg::tileReductionUsingForall()`).
This allows for the tiling of FHELinalg operations by first replacing
them with appropriate `linalg.generic` oeprations and then invoking
the tiling pass in the pipeline. In order for the tiling to take
place, tile sizes must be specified using the `tile-sizes` operation
attribute, either directly for `linalg.generic` operations or
indirectly for the FHELinalg operation, e.g.,
"FHELinalg.matmul_eint_int"(%a, %b) { "tile-sizes" = [0, 0, 7] } : ...
Tiling of operations with a reduction dimension is currently limited
to tiling of the reduction dimension, i.e., the tile sizes for the
parallel dimensions must be zero.
This adds an invocation of the `SCFForallToSCFFor` pass to the
compilation pipeline before lowering to the LLVM dialect as a
sequential fallback path to future passes exploiting the parallelism
of `scf.forall` further up in the pipeline.
This adds a new pass that converts `scf.forall` loops into nested
`scf.for` operations. The conversion carries parallel output tensors
from the original loop as dependencies through the loop nest and
replaces any occurrence of `tensor.parallel_insert_slice` operations
in the `scf.forall.in_parallel` terminator with equivalent
`tensor.insert_slice` operations.
This makes the trip counts of operations in the TFHE statistics pass
as well as the per-location memory usage statistics in the memory
usage statistics pass optional. These values are unset if the trip
count could not be determined statically.
The tests `end_to_end_leveled.jit.loop_dagmulti.mul_eint_10bits.0` and
`end_to_end_leveled.jit.loop_dagmulti.signed_mul_eint_10bits.0`
reproducibly fail on the mac2.metal instance used by the CI due to
insufficient memory. This change disables all instances of these tests
with 10 or more bits of precision on MacOS.
The Concrete Optimizer is invoked on a representation of the program
in the high-level FHELinalg / FHE Dialects and yields a solution with
a one-to-one mapping of operations to keys. However, the abstractions
used by these dialects do not allow for references to keys and the
application of the solution is delayed until the pipeline reaches a
representation of the program in the lower-level TFHE dialect. Various
transformations applied by the pipeline along the way may break the
one-to-one mapping and add indirections into producer-consumer
relationships, resulting in ambiguous or partial mappings of TFHE
operations to the keys. In particular, explicit frontiers between
optimizer partitions may not be recovered.
This commit preserves explicit frontiers between optimizer partitions
as `optimizer.partition_frontier` operations and lowers these to
keyswitch operations before parametrization of TFHE operations.
This adds a new dialect called `Optimizer` with operations related to
the Concrete Optimizer. Currently, there is only one operation
`optimizer.partition_frontier` that can be inserted between a producer
and a consumer which belong to different partitions computed by the
optimizer. The purpose of this operation is to preserve explicit key
changes from the invocation of the optimizer on high-level dialects
(i.e., FHELinalg / FHE) until the IR is provided with actual
references to keys in low-level dialects (i.e., TFHE).
The main debugging function is
`TypeInferenceUtils::dumpAllState(mlir::Operation* op)` which dumps
the entire state of type inference for the function containing `op`.
The DAG pass establishing a mapping between operations in the IR and
the optimizer DAG currently omits assignment of the optimizer ID to
`FHE.reinterpret_precision` operations via the `TFHE.OId`
attribute. This prevents subsequent passes from determining to which
optimizer partition a `FHE.reinterpret_precision` operation belongs.
This commit removes the early exit in `FunctionToDag::addOperation`
for the handling of `FHE.reinterpret_precision` that prevented the
code assigning the optimizer ID from being executed.
