Update to ROCm 4.3 manifest

* Delete AMD HIP Programming Guide_v4.2.pdf

* Delete AMD_HIP_API_Guide_4.2.pdf

* Delete AMD_ROCm_DataCenter_Tool_User_Guide_v4.2.pdf

* Delete AMD_ROCm_Release_Notes_v4.2.pdf

* Delete HIP_Supported_CUDA_API_Reference_Guide_v4.2.pdf

* Delete ROCm_Data_Center_Tool_API_Guide_v4.2.pdf

* Delete ROCm_Debugger_API_Guide_v4.2.pdf

* Delete ROCm_Debugger_User_Guide_v4.2.pdf

* Delete ROCm_SMI_Manual_4.2.pdf

* Update README.md

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* Delete latestGPU.PNG

* Delete rocsolverAPI.PNG

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README.md

@@ -1,24 +1,21 @@
+# AMD ROCm™ v4.3 Release Notes 
 
-# AMD ROCm Release Notes v3.7.0
-
-This page describes the features, fixed issues, and information about downloading and installing the ROCm software.
-It also covers known issues and deprecated features in this release.
+This document describes the features, fixed issues, and information about downloading and installing the AMD ROCm™ software. It also covers known issues and deprecations in this release.
 
 - [Supported Operating Systems and Documentation Updates](#Supported-Operating-Systems-and-Documentation-Updates)
   * [Supported Operating Systems](#Supported-Operating-Systems)
+  * [ROCm Installation Updates](#ROCm-Installation-Updates)
   * [AMD ROCm Documentation Updates](#AMD-ROCm-Documentation-Updates)
+
    
 - [What\'s New in This Release](#Whats-New-in-This-Release)
-  * [AOMP Enhancements](#AOMP-Enhancements)
-  * [Compatibility with NVIDIA Communications Collective Library v2\.7 API](#Compatibility-with-NVIDIA-Communications-Collective-Library-v27-API)
-  * [Singular Value Decomposition of Bi\-diagonal Matrices](#Singular-Value-Decomposition-of-Bi-diagonal-Matrices)
-  * [rocSPARSE_gemmi\() Operations for Sparse Matrices](#rocSPARSE_gemmi-Operations-for-Sparse-Matrices)
-    
- 
-- [Known Issues](#Known-Issues)
+  * [HIP Enhancements](#HIP-Enhancements)
+  * [ROCm Data Center Tool](#ROCm-Data-Center-Tool)
+  * [ROCm Math and Communication Libraries](#ROCm-Math-and-Communication-Libraries)
+  * [ROCProfiler Enhancements](#ROCProfiler-Enhancements)   
+
+- [Known Issues in This Release](#Known-Issues-in-This-Release)
 
-- [Deploying ROCm](#Deploying-ROCm)
- 
 - [Hardware and Software Support](#Hardware-and-Software-Support)
 
 - [Machine Learning and High Performance Computing Software Stack for AMD GPU](#Machine-Learning-and-High-Performance-Computing-Software-Stack-for-AMD-GPU)
@@ -27,30 +24,54 @@ It also covers known issues and deprecated features in this release.
   
 
 
-# Supported Operating Systems 
 
-## Support for Ubuntu 20.04 
+## ROCm Installation Updates 
+
+### Supported Operating Systems
+
+The AMD ROCm platform is designed to support the following operating systems:
+
+![Screenshot](https://github.com/Rmalavally/ROCm/blob/master/images/OSKernel.PNG)
 
 
-In this release, AMD ROCm extends support to Ubuntu 20.04, including dual-kernel.
+### Fresh Installation of AMD ROCM V4.3 Recommended
 
-## List of Supported Operating Systems
+Complete uninstallation of previous ROCm versions is required before installing a new version of ROCm. **An upgrade from previous releases to AMD ROCm v4.3 is not supported**. For more information, refer to the AMD ROCm Installation Guide at
 
-The AMD ROCm v3.7.x platform is designed to support the following operating systems:
-
-* Ubuntu 20.04 and 18.04.4 (Kernel 5.3)	
-* CentOS 7.8 & RHEL 7.8 (Kernel 3.10.0-1127) (Using devtoolset-7 runtime support)
-* CentOS 8.2 & RHEL 8.2 (Kernel 4.18.0 ) (devtoolset is not required)
-* SLES 15 SP1
-
-## Fresh Installation of AMD ROCm v3.7 Recommended
-A fresh and clean installation of AMD ROCm v3.7 is recommended. An upgrade from previous releases to AMD ROCm v3.7 is not supported.
-
-For more information, refer to the AMD ROCm Installation Guide at:
 https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html
 
 **Note**: AMD ROCm release v3.3 or prior releases are not fully compatible with AMD ROCm v3.5 and higher versions. You must perform a fresh ROCm installation if you want to upgrade from AMD ROCm v3.3 or older to 3.5 or higher versions and vice-versa.
 
+**Note**: *render* group is required only for Ubuntu v20.04. For all other ROCm supported operating systems, continue to use video group. 
+
+* For ROCm v3.5 and releases thereafter, the clinfo path is changed to /opt/rocm/opencl/bin/clinfo. 
+
+* For ROCm v3.3 and older releases, the clinfo path remains /opt/rocm/opencl/bin/x86_64/clinfo. 
+ 
+## ROCm Multi-Version Installation Update
+
+With the AMD ROCm v4.3 release, the following ROCm multi-version installation changes apply:
+
+The meta packages rocm-dkms<version> are now deprecated for multi-version ROCm installs.  For example, rocm-dkms3.7.0, rocm-dkms3.8.0.
+ 
+* Multi-version installation of ROCm should be performed by installing rocm-dev<version> using each of the desired ROCm versions. For example, rocm-dev3.7.0, rocm-dev3.8.0, rocm-dev3.9.0.   
+
+* The rock-dkms loadable kernel modules should be installed using a single rock-dkms package. 
+
+* ROCm v3.9 and above will not set any ldconfig entries for ROCm libraries for multi-version installation.  Users must set LD_LIBRARY_PATH to load the ROCm library version of choice.
+
+**NOTE**: The single version installation of the ROCm stack remains the same. The rocm-dkms package can be used for single version installs and is not deprecated at this time.
+	
+
+## Support for Enviornment Modules
+	
+Environment modules are now supported. This enhancement in the ROCm v4.3 release enables users to switch between ROCm v4.2 and ROCm v4.3 easily and efficiently. 
+	
+For more information about installing environment modules, refer to
+	
+https://modules.readthedocs.io/en/latest/
+ 
+
 
 # AMD ROCm Documentation Updates
 
@@ -58,38 +79,73 @@ https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html
 
 The AMD ROCm Installation Guide in this release includes:
 
-* Updated Supported Environments
-* HIP Installation Instructions
+* Supported Environments
 
-https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html
+* Installation Instructions 
+
+* HIP Installation Instructions 
+
+For more information, refer to the ROCm documentation website at:
+
+https://rocmdocs.amd.com/en/latest/
 
 
 ## AMD ROCm - HIP Documentation Updates
 
-### Texture and Surface Functions
-The documentation for Texture and Surface functions is updated and available at:
+* HIP Programming Guide v4.3 
+	
+https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_HIP_Programming_Guide_v4.3.pdf
+	
+* HIP API Guide v4.3
+	
+https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_HIP_API_Guide_v4.3.pdf
+	
+* HIP-Supported CUDA API Reference Guide v4.3
+	
+https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_HIP_Supported_CUDA_API_Reference_Guide_v4.3.pdf
+	
 
-https://rocmdocs.amd.com/en/latest/Programming_Guides/Kernel_language.html
-
-### Warp Shuffle Functions
-The documentation for Warp Shuffle functions is updated and available at:
-
-https://rocmdocs.amd.com/en/latest/Programming_Guides/Kernel_language.html
-
-### Compiler Defines and Environment Variables
-The documentation for the updated HIP Porting Guide is available at:
-
-https://rocmdocs.amd.com/en/latest/Programming_Guides/HIP-porting-guide.html#hip-porting-guide
+* **NEW** - AMD ROCm Compiler Reference Guide v4.3 
+	
+https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_Compiler_Reference_Guide_v4.3.pdf
+	
+* HIP FAQ
+	
+https://rocmdocs.amd.com/en/latest/Programming_Guides/HIP-FAQ.html#hip-faq
 
 
-## AMD ROCm Debug Agent
+## ROCm Data Center User and API Guide
 
-ROCm Debug Agent Library 
+* ROCm Data Center Tool User Guide
 
-https://rocmdocs.amd.com/en/latest/ROCm_Tools/rocm-debug-agent.html
+  - Prometheus (Grafana) Integration with Automatic Node Detection 
+	
+https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_ROCm_DataCenter_Tool_User_Guide_v4.3.pdf
 
+* ROCm Data Center Tool API Guide
 
-## General AMD ROCm Documentatin Links
+https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_RDC_API_Guide_v4.3.pdf
+	
+
+## ROCm SMI API Documentation Updates 
+
+* ROCm SMI API Guide 
+
+https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_ROCm_SMI_Guide_v4.3.pdf
+ 
+  
+## ROC Debugger User and API Guide 
+
+* ROC Debugger User Guide  
+	
+https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_ROCDebugger_User_Guide.pdf
+
+* Debugger API Guide 
+
+https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_ROCDebugger_API.pdf 
+	
+
+## General AMD ROCm Documentation Links
 
 Access the following links for more information:
 
@@ -103,242 +159,557 @@ Access the following links for more information:
 
 * For AMD ROCm binary structure, see
 
-  https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html#build-amd-rocm
+  https://rocmdocs.amd.com/en/latest/Installation_Guide/Software-Stack-for-AMD-GPU.html
+  
 
 * For AMD ROCm Release History, see
 
-  https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html#amd-rocm-version-history
+ https://rocmdocs.amd.com/en/latest/Current_Release_Notes/ROCm-Version-History.html
 
 
 
 # What\'s New in This Release
 
-## AOMP ENHANCEMENTS
+## HIP Enhancements
 
-AOMP is a scripted build of LLVM. It supports OpenMP target offload on AMD GPUs. Since AOMP is a Clang/LLVM compiler, it also supports GPU offloading with HIP, CUDA, and OpenCL.
+### HIP Versioning Update
 
-The following enhancements are made for AOMP in this release: 
-* OpenMP 5.0 is enabled by default. You can use -fopenmp-version=45 for OpenMP 4.5 compliance
-* Restructured to include the ROCm compiler
-* B=Bitcode search path using hip policy HIP_DEVICE_LIB_PATH and hip-devic-lib command line option to enable global_free for kmpc_impl_free
+The HIP version definition is updated from the ROCm v4.2 release as follows: 
 
-Restructured hostrpc, including:
-* Replaced hostcall register functions with handlePayload(service, payload). Note, handlPayload has a simple switch to call the correct service handler function.
-* Removed the WITH_HSA macro
-* Moved the hostrpc stubs and host fallback functions into a single library and the include file. This enables the stubs openmp cpp source instead of hip and reorganizes the directory openmp/libomptarget/hostrpc.
-* Moved hostrpc_invoke.cl to DeviceRTLs/amdgcn.
-* Generalized the vargs processing in printf to work for any vargs function to execute on the host, including a vargs function that uses a function pointer.
-* Reorganized files, added global_allocate and global_free.
-* Fixed llvm TypeID enum to match the current upstream llvm TypeID.
-* Moved strlen_max function inside the declare target #ifdef _DEVICE_GPU in hostrpc.cpp to resolve linker failure seen in pfspecifier_str smoke test.
-* Fixed AOMP_GIT_CHECK_BRANCH in aomp_common_vars to not block builds in Red Hat if the repository is on a specific commit hash.
-* Simplified and reduced the size of openmp host runtime
-* Switched to default OpenMP 5.0
+```
+	HIP_VERSION=HIP_VERSION_MAJOR * 10000000 + HIP_VERSION_MINOR * 100000 + 
+	HIP_VERSION_PATCH)
+```
 
-For more information, see https://github.com/ROCm-Developer-Tools/aomp
-     
-
-## ROCm COMMUNICATIONS COLLECTIVE LIBRARY
-
-### Compatibility with NVIDIA Communications Collective Library v2\.7 API
-
-ROCm Communications Collective Library (RCCL) is now compatible with the NVIDIA Communications Collective Library (NCCL) v2.7 API.
-
-RCCL (pronounced "Rickle") is a stand-alone library of standard collective communication routines for GPUs, implementing all-reduce, all-gather, reduce, broadcast, reduce-scatter, gather, scatter, and all-to-all. There is also initial support for direct GPU-to-GPU send and receive operations. It has been optimized to achieve high bandwidth on platforms using PCIe, xGMI as well as networking using InfiniBand Verbs or TCP/IP sockets. RCCL supports an arbitrary number of GPUs installed in a single node or multiple nodes, and can be used in either single- or multi-process (e.g., MPI) applications.
-
-The collective operations are implemented using ring and tree algorithms and have been optimized for throughput and latency. For best performance, small operations can be either batched into larger operations or aggregated through the API.
-
-For more information about RCCL APIs and compatibility with NCCL v2.7, see
-https://rccl.readthedocs.io/en/develop/index.html
+The HIP version can be queried from a HIP API call
 
 
-## Singular Value Decomposition of Bi\-diagonal Matrices
+```	
+	hipRuntimeGetVersion(&runtimeVersion);	
+```
+	
+**Note**: The version returned will be greater than the version in previous ROCm releases.
 
-Rocsolver_bdsqr now computes the Singular Value Decomposition (SVD) of bi-diagonal matrices. It is an auxiliary function for the SVD of general matrices (function rocsolver_gesvd). 
+	
+### Support for Managed Memory Allocation
 
-BDSQR computes the singular value decomposition (SVD) of a n-by-n bidiagonal matrix B.
+HIP now supports and automatically manages Heterogeneous Memory Management (HMM) allocation. The HIP application performs a capability check before making the managed memory API call hipMallocManaged.
 
-The SVD of B has the following form:
+**Note**: The _managed_ keyword is unsupported currently. 
 
-B = Ub * S * Vb'
-where 
-•	S is the n-by-n diagonal matrix of singular values of B
-•	the columns of Ub are the left singular vectors of B
-•	the columns of Vb are its right singular vectors
+```
+	int managed_memory = 0;
+	HIPCHECK(hipDeviceGetAttribute(&managed_memory,
+ 	 hipDeviceAttributeManagedMemory,p_gpuDevice));
+	if (!managed_memory ) {
+  	printf ("info: managed memory access not supported on the device %d\n Skipped\n", p_gpuDevice);
+	}
+	else {
+ 	 HIPCHECK(hipSetDevice(p_gpuDevice));
+  	HIPCHECK(hipMallocManaged(&Hmm, N * sizeof(T)));
+	. . .
+	}
+```
 
-The computation of the singular vectors is optional; this function accepts input matrices U (of size nu-by-n) and V (of size n-by-nv) that are overwritten with U*Ub and Vb’*V. If nu = 0 no left vectors are computed; if nv = 0 no right vectors are computed.
+### Kernel Enqueue Serialization
 
-Optionally, this function can also compute Ub’*C for a given n-by-nc input matrix C.
+Developers can control kernel command serialization from the host using the following environment variable,
+AMD_SERIALIZE_KERNEL
+	
+* AMD_SERIALIZE_KERNEL = 1, Wait for completion before enqueue,
 
-PARAMETERS
+* AMD_SERIALIZE_KERNEL = 2, Wait for completion after enqueue,
 
-•	[in] handle: rocblas_handle.
+* AMD_SERIALIZE_KERNEL = 3, Both.
 
-•	[in] uplo: rocblas_fill.
-
-Specifies whether B is upper or lower bidiagonal.
-
-•	[in] n: rocblas_int. n >= 0.
-
-The number of rows and columns of matrix B.
-
-•	[in] nv: rocblas_int. nv >= 0. 
-
-The number of columns of matrix V.
-
-•	[in] nu: rocblas_int. nu >= 0. 
-
-The number of rows of matrix U.
-
-•	[in] nc: rocblas_int. nu >= 0. 
-
-The number of columns of matrix C.
-
-•	[inout] D: pointer to real type. Array on the GPU of dimension n.
-
-On entry, the diagonal elements of B. On exit, if info = 0, the singular values of B in decreasing order; if info > 0, the diagonal elements of a bidiagonal matrix orthogonally equivalent to B.
-
-•	[inout] E: pointer to real type. Array on the GPU of dimension n-1.
-
-On entry, the off-diagonal elements of B. On exit, if info > 0, the off-diagonal elements of a bidiagonal matrix orthogonally equivalent to B (if info = 0 this matrix converges to zero).
-
-•	[inout] V: pointer to type. Array on the GPU of dimension ldv*nv.
-
-On entry, the matrix V. On exit, it is overwritten with Vb’*V. (Not referenced if nv = 0).
-
-•	[in] ldv: rocblas_int. ldv >= n if nv > 0, or ldv >=1 if nv = 0.
-
-Specifies the leading dimension of V.
-
-•	[inout] U: pointer to type. Array on the GPU of dimension ldu*n.
-
-On entry, the matrix U. On exit, it is overwritten with U*Ub. (Not referenced if nu = 0).
-
-•	[in] ldu: rocblas_int. ldu >= nu.
-
-Specifies the leading dimension of U.
-
-•	[inout] C: pointer to type. Array on the GPU of dimension ldc*nc.
-
-On entry, the matrix C. On exit, it is overwritten with Ub’*C. (Not referenced if nc = 0).
-
-•	[in] ldc: rocblas_int. ldc >= n if nc > 0, or ldc >=1 if nc = 0.
-
-Specifies the leading dimension of C.
-
-•	[out] info: pointer to a rocblas_int on the GPU.
-
-If info = 0, successful exit. If info = i > 0, i elements of E have not converged to zero.
-
-For more information, see
-https://rocsolver.readthedocs.io/en/latest/userguide_api.html#rocsolver-type-bdsqr
+This environment variable setting enables HIP runtime to wait for GPU idle before/after any GPU command.
 
 
-### rocSPARSE_gemmi\() Operations for Sparse Matrices
+### NUMA-aware Host Memory Allocation
+	
+The Non-Uniform Memory Architecture (NUMA) policy determines how memory is allocated and selects a CPU closest to each GPU. 
+	
+NUMA also measures the distance between the GPU and CPU devices. By default, each GPU selects a Numa CPU node that has the least NUMA distance between them; the host memory is automatically allocated closest to the memory pool of the NUMA node of the current GPU device. 
+	
+Note, using the *hipSetDevice* API with a different GPU provides access to the host allocation. However, it may have a longer NUMA distance.
 
-This enhancement provides a dense matrix sparse matrix multiplication using the CSR storage format.
-rocsparse_gemmi multiplies the scalar αα with a dense m×km×k matrix AA and the sparse k×nk×n matrix BB defined in the CSR storage format, and adds the result to the dense m×nm×n matrix CC that is multiplied by the scalar ββ, such that
-C:=α⋅op(A)⋅op(B)+β⋅CC:=α⋅op(A)⋅op(B)+β⋅C
-with
 
-op(A)=⎧⎩⎨⎪⎪A,AT,AH,if trans_A == rocsparse_operation_noneif trans_A == rocsparse_operation_transposeif trans_A == rocsparse_operation_conjugate_transposeop(A)={A,if trans_A == rocsparse_operation_noneAT,if trans_A == rocsparse_operation_transposeAH,if trans_A == rocsparse_operation_conjugate_transpose
+### New Atomic System Scope Atomic Operations
+	
+HIP now provides new APIs with _system as a suffix to support system scope atomic operations. For example,  atomicAnd atomic is dedicated to the GPU device, and atomicAnd_system allows developers to extend the atomic operation to system scope from the GPU device to other CPUs and GPU devices in the system.
+	
+For more information, refer to the HIP Programming Guide at,
+	
+https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_HIP_Programming_Guide_v4.3.pdf
 
-and
+### Indirect Function Call and C++ Virtual Functions 
+	
+While the new release of the ROCm compiler supports indirect function calls and C++ virtual functions on a device, there are some known limitations and issues. 
+	
+**Limitations**
+	
+* An address to a function is device specific.  Note, a function address taken on the host can not be used on a device, and a function address taken on a device can not be used on the host.  On a system with multiple devices, an address taken on one device can not be used on a different device.
+	
+* C++ virtual functions only work on the device where the object was constructed.
+	
+* Indirect call to a device function with function scope shared memory allocation is not supported. For example, LDS.
+	
+* Indirect call to a device function defined in a source file different than the calling function/kernel is only supported when compiling the entire program with -fgpu-rdc.
+	
+**Known Issues in This Release**
+	
+* Programs containing kernels with different launch bounds may crash when making an indirect function call.  This issue is due to a compiler issue miscalculating the register budget for the callee function.
+	
+* Programs may not work correctly when making an indirect call to a function that uses more resources. For example, scratch memory, shared memory, registers made available by the caller.
+	
+* Compiling a program with objects with pure or deleted virtual functions on the device will result in a linker error.  This issue is due to the missing implementation of some C++ runtime functions on the device.
+	
+* Constructing an object with virtual functions in private or shared memory may crash the program due to a compiler issue when generating code for the constructor.  
 
-op(B)=⎧⎩⎨⎪⎪B,BT,BH,if trans_B == rocsparse_operation_noneif trans_B == rocsparse_operation_transposeif trans_B == rocsparse_operation_conjugate_transposeop(B)={B,if trans_B == rocsparse_operation_noneBT,if trans_B == rocsparse_operation_transposeBH,if trans_B == rocsparse_operation_conjugate_transpose
-Note: This function is non-blocking and executed asynchronously with the host. It may return before the actual computation has finished.
 
-For more information and examples, see
-https://rocsparse.readthedocs.io/en/master/usermanual.html#rocsparse-gemmi
- 
+## ROCm Data Center Tool 
+
+### Prometheus (Grafana) Integration with Automatic Node Detection 
+
+The ROCm Data Center (RDC) tool enables you to use Consul to discover the rdc_prometheus service automatically. Consul is “a service mesh solution providing a full-featured control plane with service discovery, configuration, and segmentation functionality.” For more information, refer to their website at https://www.consul.io/docs/intro.
+	
+The ROCm Data Center Tool uses Consul for health checks of RDC’s integration with the Prometheus plug-in (rdc_prometheus), and these checks provide information on its efficiency.  
+	
+Previously, when a new compute node was added, users had to change prometheus_targets.json to use Consul manually. Now, with the Consul agent integration, a new compute node can be discovered automatically.
+	
+https://github.com/RadeonOpenCompute/ROCm/blob/master/AMD_ROCm_DataCenter_Tool_User_Guide_v4.3.pdf
+
+### Coarse Grain Utilization
+	
+This feature provides a counter that displays the coarse grain GPU usage information, as shown below.
+	
+Sample output
+
+```
+		$ rocm_smi.py --showuse
+		============================== % time GPU is busy =============================
+               GPU[0] : GPU use (%): 0
+               GPU[0] : GFX Activity: 3401
+```
+
+	
+### Add 64-bit Energy Accumulator In-band
+	
+This feature provides an average value of energy consumed over time in a free-flowing RAPL counter, a 64-bit Energy Accumulator.
+	
+Sample output
+	
+```
+	$ rocm_smi.py --showenergycounter
+	=============================== Consumed Energy ================================
+	GPU[0] : Energy counter: 2424868
+	GPU[0] : Accumulated Energy (uJ): 0.0	
+
+```	
+	
+### Support for Continuous Clocks Values
+	
+ROCm SMI will support continuous clock values instead of the previous discrete levels. Moving forward the updated sysfs file will consist of only MIN and MAX values and the user can set the clock value in the given range. 
+	
+Sample output:
+
+```
+	$ rocm_smi.py --setsrange 551 1270 
+	Do you accept these terms? [y/N] y                                                                                    
+	============================= Set Valid sclk Range=======
+	GPU[0]          : Successfully set sclk from 551(MHz) to 1270(MHz)                                                     
+	GPU[1]          : Successfully set sclk from 551(MHz) to 1270(MHz)                                                     
+	=========================================================================
+                       
+	$ rocm_smi.py --showsclkrange                                                                                                                                                                    
+	============================ Show Valid sclk Range======                     
+
+	GPU[0]          : Valid sclk range: 551Mhz - 1270Mhz                                                                  
+	GPU[1]          : Valid sclk range: 551Mhz - 1270Mhz             
+```
+	
+### Memory Utilization Counters
+
+This feature provides a counter display memory utilization information as shown below.
+
+Sample output
+	
+```
+       $ rocm_smi.py --showmemuse
+	========================== Current Memory Use ==============================
+
+	GPU[0] : GPU memory use (%): 0
+	GPU[0] : Memory Activity: 0
+```	
+
+### Performance Determinism
+
+ROCm SMI supports performance determinism as a unique mode of operation. Performance variations are minimal as this enhancement allows users to control the entry and exit to set a soft maximum (ceiling) for the GFX clock.
+	
+Sample output
+
+```
+	$ rocm_smi.py --setperfdeterminism 650
+	cat pp_od_clk_voltage
+	GFXCLK:                
+	0: 500Mhz
+	1: 650Mhz *
+	2: 1200Mhz
+	$ rocm_smi.py --resetperfdeterminism 	
+```	
+	
+**Note**: The idle clock will not take up higher clock values if no workload is running. After enabling determinism, users can run a GFX workload to set performance determinism to the desired clock value in the valid range.
+
+	* GFX clock could either be less than or equal to the max value set in this mode. GFX clock will be at the max clock set in this mode only when required by the running 	workload.
+	
+	* VDDGFX will be higher by an offset (75mv or so based on PPTable) in the determinism mode.
+	
+### HBM Temperature Metric Per Stack
+
+This feature will enable ROCm SMI to report all HBM temperature values as shown below.
+
+Sample output
+
+```	
+   	$ rocm_smi.py –showtemp
+	================================= Temperature =================================
+	GPU[0] : Temperature (Sensor edge) (C): 29.0
+	GPU[0] : Temperature (Sensor junction) (C): 36.0
+	GPU[0] : Temperature (Sensor memory) (C): 45.0
+	GPU[0] : Temperature (Sensor HBM 0) (C): 43.0
+	GPU[0] : Temperature (Sensor HBM 1) (C): 42.0
+	GPU[0] : Temperature (Sensor HBM 2) (C): 44.0
+	GPU[0] : Temperature (Sensor HBM 3) (C): 45.0
+```	
+
+	
+## ROCm Math and Communication Libraries 
+
+### rocBLAS
+
+**Optimizations**
+
+* Improved performance of non-batched and batched rocblas_Xgemv for gfx908 when m <= 15000 and n <= 15000
+	
+* Improved performance of non-batched and batched rocblas_sgemv and rocblas_dgemv for gfx906 when m <= 6000 and n <= 6000
+	
+* Improved the overall performance of non-batched and batched rocblas_cgemv for gfx906
+	
+* Improved the overall performance of rocblas_Xtrsv
+
+For more information, refer to 
+
+https://rocblas.readthedocs.io/en/master/
+
+
+### rocRAND
+
+**Enhancements**
+	
+* gfx90a support added
+	
+* gfx1030 support added
+
+* gfx803 supported re-enabled
+
+**Fixed**
+	
+* Memory leaks in Poisson tests has been fixed.
+	
+* Memory leaks when generator has been created but setting seed/offset/dimensions display an exception has been fixed.
+
+For more information, refer to
+
+https://rocrand.readthedocs.io/en/latest/
+
+
+### rocSOLVER	
+
+**Enhancements**
+	
+Linear solvers for general non-square systems:
+	
+* GELS now supports underdetermined and transposed cases
+	
+* Inverse of triangular matrices
+	
+* TRTRI (with batched and strided_batched versions)
+	
+* Out-of-place general matrix inversion
+	
+* GETRI_OUTOFPLACE (with batched and strided_batched versions)
+	
+* Argument names for the benchmark client now match argument names from the public API
+	
+**Fixed Issues**
+	
+* Known issues with Thin-SVD. The problem was identified in the test specification, not in the thin-SVD implementation or the rocBLAS gemm_batched routines.
+
+* Benchmark client longer crashes as a result of leading dimension or stride arguments not being provided on the command line.
+
+**Optimizations**
+	
+* Improved general performance of matrix inversion (GETRI)
+
+For more information, refer to
+
+https://rocsolver.readthedocs.io/en/latest/
+
+
+### rocSPARSE	
+	
+**Enhancements**
+	
+* (batched) tridiagonal solver with and without pivoting
+	
+* dense matrix sparse vector multiplication (gemvi)
+	
+* support for gfx90a
+	
+* sampled dense-dense matrix multiplication (sddmm)
+	
+**Improvements**
+	
+* client matrix download mechanism
+	
+* boost dependency in clients removed
+
+
+For more information, refer to
+
+https://rocsparse.readthedocs.io/en/latest/usermanual.html#rocsparse-gebsrmv
+
+
+### hipBLAS
+
+**Enhancements**
+	
+* Added *hipblasStatusToString*
+	
+**Fixed**
+	
+* Added catch() blocks around API calls to prevent the leak of C++ exceptions
+	
+
+### rocFFT
+
+**Changes**
+	
+* Re-split device code into single-precision, double-precision, and miscellaneous kernels.
+	
+**Fixed Issues**
+	
+* double-precision planar->planar transpose.
+	
+* 3D transforms with unusual strides, for SBCC-optimized sizes.
+	
+* Improved buffer placement logic.
+
+For more information, refer to
+
+https://rocfft.readthedocs.io/en/rocm-4.3.0/
+	
+
+### hipFFT	
+
+**Fixed Issues**
+	
+* CMAKE updates
+	
+* Added callback API in hipfftXt.h header.
+
+
+### rocALUTION
+	
+**Enhancements**
+	
+* Support for gfx90a target
+	
+* Support for gfx1030 target
+	
+**Improvements**
+	
+* Install script
+	
+For more information, refer to
+	
+### rocTHRUST	
+
+**Enhancements**
+	
+* Updated to match upstream Thrust 1.11
+	
+* gfx90a support added
+	
+* gfx803 support re-enabled
+
+hipCUB	
+
+Enhancements
+
+* DiscardOutputIterator to backend header
+	
+
+## ROCProfiler Enhancements
+
+### Tracing Multiple MPI Ranks 
+
+When tracing multiple MPI ranks in ROCm v4.3, users must use the form:
+
+```
+	mpirun ... <mpi args> ... rocprof ... <rocprof args> ... application ... <application args>
+	
+```
+
+**NOTE**: This feature differs from ROCm v4.2 (and lower), which used "rocprof ... mpirun ... application".
+	
+This change was made to enable ROCProfiler to handle process forking better and launching via mpirun (and related) executables. 
+
+From a user perspective, this new execution mode requires:
+	
+1. Generation of trace data per MPI (or process) rank.
+	
+2. Use of a new "merge_traces.sh" utility script (see: <insert link here>) to combine traces from multiple processes into a unified trace for profiling.
+	
+For example, to accomplish step #1, ROCm provides a simple bash wrapper that demonstrates how to generate a unique output directory per process:
+	
+```
+	$ cat wrapper.sh
+	#! /usr/bin/env bash
+	if [[ -n ${OMPI_COMM_WORLD_RANK+z} ]]; then
+ 	 # mpich
+  	export MPI_RANK=${OMPI_COMM_WORLD_RANK}
+	elif [[ -n ${MV2_COMM_WORLD_RANK+z} ]]; then
+  	# ompi
+  	export MPI_RANK=${MV2_COMM_WORLD_RANK}
+	fi
+	args="$*"
+	pid="$$"
+	outdir="rank_${pid}_${MPI_RANK}"
+	outfile="results_${pid}_${MPI_RANK}.csv"
+	eval "rocprof -d ${outdir} -o ${outdir}/${outfile} $*"
+```
+
+This script:
+	
+* Determines the global MPI rank (implemented here for OpenMPI and MPICH only)
+	
+* Determines the process id of the MPI rank
+	
+* Generates a unique output directory using the two
+
+To invoke this wrapper, use the following command:
+
+```
+	mpirun <mpi args> ./wrapper.sh --hip-trace <application> <args>
+```
+
+This generates an output directory for each used MPI rank. For example, 	
+
+```
+	$ ls -ld rank_* | awk {'print $5" "$9'}
+	4096 rank_513555_0
+	4096 rank_513556_1
+```	
+	
+Finally, these traces may be combined using the merge traces script (<insert link here>). For example, 
+
+```
+	$  ./merge_traces.sh -h
+	Script for aggregating results from multiple rocprofiler out directries.
+	Full path: /opt/rocm/bin/merge_traces.sh
+	Usage:
+  	merge_traces.sh -o <outputdir> [<inputdir>...]
+```	
+
+Use the following input arguments to the merge_traces.sh script to control which traces are merged and where the resulting merged trace is saved.
+	
+* -o <*outputdir*> - output directory where the results are aggregated.
+	
+* <*inputdir*>... - space-separated list of rocprofiler directories. If not specified, CWD is used.
+
+The file 'unified/results.json' is generated,  and the resulting unified/results.json file contains trace data from both MPI ranks. 
+
+Known issue for ROCProfiler
+	
+Collecting several counter collection passes (multiple "pmc:" lines in an counter input file) is not supported in a single run.  
+The workaround is to break the multiline counter input file into multiple single-line counter input files and execute runs.
+
+	
+# Known Issues in This Release
 
-# Known Issues 
 The following are the known issues in this release.
 
-## (AOMP) ‘Undefined Hidden Symbol’ Linker Error Causes Compilation Failure in HIP
+## Upgrade to AMD ROCm v4.3 Not Supported
 
-The HIP example device_lib fails to compile due to unreferenced symbols with Link Time Optimization resulting in ‘undefined hidden symbol’ errors. 
+An upgrade from previous releases to AMD ROCm v4.2 is not supported. Complete uninstallation of previous ROCm versions is required before installing a new version of ROCm.
+	
+## _LAUNCH BOUNDS_Ignored During Kernel Launch
 
-This issue is under investigation and there is no known workaround at this time.
-
-
-## MIGraphX Fails for fp16 Datatype
-The MIGraphX functionality does not work for the fp16 datatype.  
-
-The following workaround is recommended: 
-
-Use the AMD ROCm v3.3 of MIGraphX 
-
-Or
-
-Build MIGraphX v3.7 from the source using AMD ROCm v3.3
-
-## Missing Google Test Installation May Cause RCCL Unit Test Compilation Failure
-Users of the RCCL install.sh script may encounter an RCCL unit test compilation error. It is recommended to use CMAKE directly instead of install.sh to compile RCCL. Ensure Google Test 1.10+ is available in the CMAKE search path.
-
-
-As a workaround, use the latest RCCL from the GitHub development branch at:
-https://github.com/ROCmSoftwarePlatform/rccl/pull/237
-
-
-## Issue with Peer-to-Peer Transfers 
-Using peer-to-peer (P2P) transfers on systems without the hardware P2P assistance may produce incorrect results.
-
-Ensure the hardware supports peer-to-peer transfers and enable the peer-to-peer setting in the hardware to resolve this issue. 
-
-
-## Partial Loss of Tracing Events for Large Applications
-An internal tracing buffer allocation issue can cause a partial loss of some tracing events for large applications.
-
-As a workaround, rebuild the roctracer/rocprofiler libraries from the GitHub ‘roc-3.7’ branch at:
-•	https://github.com/ROCm-Developer-Tools/rocprofiler
-•	https://github.com/ROCm-Developer-Tools/roctracer
-
-
-## GPU Kernel C++ Names Not Demangled
-GPU kernel C++ names in the profiling traces and stats produced by ‘—hsa-trace’ option are not demangled.
-
-As a workaround, users may choose to demangle the GPU kernel C++ names as required.
-
-
-## ‘rocprof’ option ‘--parallel-kernels’ Not Supported in This Release
-
-‘rocprof’ option ‘--parallel-kernels’ is available in the options list, however,  it is not fully validated and supported in this release.
-
-## Random Soft Hang Observed When Running ResNet-Based Models
-
-A random soft hang is observed when running ResNet-based models for a loop run of more than 25 to 30 hours.  The issue is observed on both PyTorch and TensorFlow frameworks.
-You can terminate the unresponsive process to temporarily resolve the issue.
-
-There is no known workaround at this time.
+The HIP runtime returns the hipErrorLaunchFailure error code when an application tries to launch kernel with a block size larger than the launch bounds mentioned during compile time. If no launch bounds were specified during the compile time, the default value of 1024 is assumed.  Refer to the HIP trace for more information about the failing kernel. A sample error in the trace is shown below:
+ 
+Snippet of the HIP trace
+	
+```
+	:3:devprogram.cpp           :2504: 2227377746776 us: Using Code Object V4.
+	:3:hip_module.cpp           :361 : 2227377768546 us: 7670 : [7f7c6eddd180] ihipModuleLaunchKernel ( 0x0x16fe080, 2048, 1, 1, 		1024, 1, 1, 0, stream:<null>, 0x7ffded8ad260, char array:<null>, event:0, event:0, 0, 0 )
+	:1:hip_module.cpp           :254 : 2227377768572 us: Launch params (1024, 1, 1) are larger than launch bounds (64) for 		kernel _Z8MyKerneliPd
+	:3:hip_platform.cpp         :667 : 2227377768577 us: 7670 : [7f7c6eddd180] ihipLaunchKernel: Returned hipErrorLaunchFailure 		:
+	:3:hip_module.cpp           :493 : 2227377768581 us: 7670 : [7f7c6eddd180] hipLaunchKernel: Returned hipErrorLaunchFailure :
+```
 
+There is no known workaround at this time. 
+	
+## PYCACHE Folder Exists After ROCM SMI Library Uninstallation
+	
+Users may observe that the /opt/rocm-x/bin/__pycache__ folder continues to exist even after the rocm_smi_lib uninstallation.
+Workaround: Delete the /opt/rocm-x/bin/__pycache__ folder manually before uninstalling rocm_smi_lib.
 
 
 # Deploying ROCm
-AMD hosts both Debian and RPM repositories for the ROCm v3.7.x packages. 
+
+AMD hosts both Debian and RPM repositories for the ROCm packages. 
 
 For more information on ROCM installation on all platforms, see
 
 https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html
 
+
+# Machine Learning and High Performance Computing Software Stack for AMD GPU
+
+For an updated version of the software stack for AMD GPU, see
+
+https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html#software-stack-for-amd-gpu
+
+
+
 # Hardware and Software Support
 ROCm is focused on using AMD GPUs to accelerate computational tasks such as machine learning, engineering workloads, and scientific computing.
 In order to focus our development efforts on these domains of interest, ROCm supports a targeted set of hardware configurations which are detailed further in this section.
 
+**Note:** The AMD ROCm™ open software platform is a compute stack for headless system deployments. GUI-based software applications are currently not supported.
+
 #### Supported GPUs
 Because the ROCm Platform has a focus on particular computational domains, we offer official support for a selection of AMD GPUs that are designed to offer good performance and price in these domains.
 
+**Note:** The integrated GPUs of Ryzen are not officially supported targets for ROCm.
+
 ROCm officially supports AMD GPUs that use following chips:
 
-  * GFX8 GPUs
-    * "Fiji" chips, such as on the AMD Radeon R9 Fury X and Radeon Instinct MI8
-    * "Polaris 10" chips, such as on the AMD Radeon RX 580 and Radeon Instinct MI6
-  * GFX9 GPUs
-    * "Vega 10" chips, such as on the AMD Radeon RX Vega 64 and Radeon Instinct MI25
-    * "Vega 7nm" chips, such as on the Radeon Instinct MI50, Radeon Instinct MI60 or AMD Radeon VII
+* GFX9 GPUs
+
+  - "Vega 10" chips, such as on the AMD Radeon RX Vega 64 and Radeon Instinct MI25
+  
+  - "Vega 7nm" chips, such as on the Radeon Instinct MI50, Radeon Instinct MI60 or AMD Radeon VII, Radeon Pro VII
+
+* CDNA GPUs
+
+  - MI100 chips such as on the AMD Instinct™ MI100
+
 
 ROCm is a collection of software ranging from drivers and runtimes to libraries and developer tools.
 Some of this software may work with more GPUs than the "officially supported" list above, though AMD does not make any official claims of support for these devices on the ROCm software platform.
+
 The following list of GPUs are enabled in the ROCm software, though full support is not guaranteed:
 
   * GFX8 GPUs
@@ -354,7 +725,7 @@ As described [below](#limited-support), "Carrizo", "Bristol Ridge", and "Raven R
 However, they are not enabled in the HIP runtime, and may not work due to motherboard or OEM hardware limitations.
 As such, they are not yet officially supported targets for ROCm.
 
-For a more detailed list of hardware support, please see [the following documentation](https://rocm.github.io/hardware.html).
+For a more detailed list of hardware support, please see [the following documentation](https://en.wikipedia.org/wiki/List_of_AMD_graphics_processing_units).
 
 #### Supported CPUs
 As described above, GFX8 GPUs require PCIe 3.0 with PCIe atomics in order to run ROCm.
@@ -394,9 +765,10 @@ does not require or take advantage of PCIe Atomics. However, we still recommend
 from the list provided above for compatibility purposes.
 
 #### Not supported or limited support under ROCm
+
 ##### Limited support
 
-* ROCm 2.9.x should support PCIe 2.0 enabled CPUs such as the AMD Opteron, Phenom, Phenom II, Athlon, Athlon X2, Athlon II and older Intel Xeon and Intel Core Architecture and Pentium CPUs. However, we have done very limited testing on these configurations, since our test farm has been catering to CPUs listed above. This is where we need community support. _If you find problems on such setups, please report these issues_.
+* ROCm 4.x should support PCIe 2.0 enabled CPUs such as the AMD Opteron, Phenom, Phenom II, Athlon, Athlon X2, Athlon II and older Intel Xeon and Intel Core Architecture and Pentium CPUs. However, we have done very limited testing on these configurations, since our test farm has been catering to CPUs listed above. This is where we need community support. _If you find problems on such setups, please report these issues_.
 * Thunderbolt 1, 2, and 3 enabled breakout boxes should now be able to work with ROCm. Thunderbolt 1 and 2 are PCIe 2.0 based, and thus are only supported with GPUs that do not require PCIe 3.1.0 atomics (e.g. Vega 10). However, we have done no testing on this configuration and would need community support due to limited access to this type of equipment.
 * AMD "Carrizo" and "Bristol Ridge" APUs are enabled to run OpenCL, but do not yet support HIP or our libraries built on top of these compilers and runtimes.
   * As of ROCm 2.1, "Carrizo" and "Bristol Ridge" require the use of upstream kernel drivers.
@@ -409,11 +781,13 @@ from the list provided above for compatibility purposes.
 
 ##### Not supported
 
-* "Tonga", "Iceland", "Vega M", and "Vega 12" GPUs are not supported in ROCm 2.9.x
+* "Tonga", "Iceland", "Vega M", and "Vega 12" GPUs are not supported.
 * We do not support GFX8-class GPUs (Fiji, Polaris, etc.) on CPUs that do not have PCIe 3.0 with PCIe atomics.
   * As such, we do not support AMD Carrizo and Kaveri APUs as hosts for such GPUs.
   * Thunderbolt 1 and 2 enabled GPUs are not supported by GFX8 GPUs on ROCm. Thunderbolt 1 & 2 are based on PCIe 2.0.
 
+In the default ROCm configuration, GFX8 and GFX9 GPUs require PCI Express 3.0 with PCIe atomics. The ROCm platform leverages these advanced capabilities to allow features such as user-level submission of work from the host to the GPU. This includes PCIe atomic Fetch and Add, Compare and Swap, Unconditional Swap, and AtomicOp Completion.
+
 #### ROCm support in upstream Linux kernels
 
 As of ROCm 1.9.0, the ROCm user-level software is compatible with the AMD drivers in certain upstream Linux kernels.
@@ -440,9 +814,17 @@ For users that have the option of using either AMD's or the upstreamed driver, t
 |      |   | Does not include most up-to-date firmware |
 
 
+# Disclaimer
 
-## Machine Learning and High Performance Computing Software Stack for AMD GPU
+AMD®, the AMD Arrow logo, AMD Instinct™, Radeon™, ROCm® and combinations thereof are trademarks of Advanced Micro Devices, Inc.
 
-For an updated version of the software stack for AMD GPU, see
+Linux® is the registered trademark of Linus Torvalds in the U.S. and other countries.
+
+PCIe® is a registered trademark of PCI-SIG Corporation. Other product names used in this publication are for identification purposes only and may be trademarks of their respective companies.  
+
+Google®  is a registered trademark of Google LLC.
+
+Ubuntu and the Ubuntu logo are registered trademarks of Canonical Ltd.
+
+Other product names used in this publication are for identification purposes only and may be trademarks of their respective companies.
 
-https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html#machine-learning-and-high-performance-computing-software-stack-for-amd-gpu-v3-5-0

default.xml

@@ -1,27 +1,26 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <manifest>
     <remote name="roc-github"
-            fetch="http://github.com/RadeonOpenCompute/" />
+fetch="http://github.com/RadeonOpenCompute/" />
     <remote name="rocm-devtools"
-            fetch="https://github.com/ROCm-Developer-Tools/" />
+fetch="https://github.com/ROCm-Developer-Tools/" />
     <remote name="rocm-swplat"
-            fetch="https://github.com/ROCmSoftwarePlatform/" />
+fetch="https://github.com/ROCmSoftwarePlatform/" />
     <remote name="gpuopen-libs"
-            fetch="https://github.com/GPUOpen-ProfessionalCompute-Libraries/" />
+fetch="https://github.com/GPUOpen-ProfessionalCompute-Libraries/" />
     <remote name="gpuopen-tools"
-            fetch="https://github.com/GPUOpen-Tools/" />
+fetch="https://github.com/GPUOpen-Tools/" />
     <remote name="KhronosGroup"
-            fetch="https://github.com/KhronosGroup/" />
-    <default revision="refs/tags/rocm-3.7.0"
-             remote="roc-github"
-             sync-c="true"
-             sync-j="4" />
-    <!--list of projects for ROCM-->
+fetch="https://github.com/KhronosGroup/" />
+    <default revision="refs/tags/rocm-4.3.0"
+     remote="roc-github"
+     sync-c="true"
+     sync-j="4" />
+<!--list of projects for ROCM-->
     <project name="ROCK-Kernel-Driver" />
     <project name="ROCT-Thunk-Interface" />
     <project name="ROCR-Runtime" />
-    <project name="ROC-smi" />
-    <project name="rocm_smi_lib" remote="roc-github" />
+    <project name="rocm_smi_lib" />
     <project name="rocm-cmake" />
     <project name="rocminfo" />
     <project name="rocprofiler" remote="rocm-devtools" />
@@ -29,26 +28,30 @@
     <project name="ROCm-OpenCL-Runtime" />
     <project path="ROCm-OpenCL-Runtime/api/opencl/khronos/icd" name="OpenCL-ICD-Loader" remote="KhronosGroup" revision="6c03f8b58fafd9dd693eaac826749a5cfad515f8" />
     <project name="clang-ocl" />
-    <!--HIP Projects-->
+<!--HIP Projects-->
     <project name="HIP" remote="rocm-devtools" />
     <project name="HIP-Examples" remote="rocm-devtools" />
     <project name="ROCclr" remote="rocm-devtools" />
     <project name="HIPIFY" remote="rocm-devtools" />
-    <!-- The following projects are all associated with the AMDGPU LLVM compiler -->
-    <project name="llvm-project" path="llvm_amd-stg-open" />
+<!-- The following projects are all associated with the AMDGPU LLVM compiler -->
+    <project name="llvm-project" />
     <project name="ROCm-Device-Libs" />
     <project name="atmi" />
     <project name="ROCm-CompilerSupport" />
-    <project name="rocr_debug_agent" remote="rocm-devtools" revision="refs/tags/roc-3.7.0" />
+    <project name="rocr_debug_agent" remote="rocm-devtools" />
     <project name="rocm_bandwidth_test" />
+    <project name="half" remote="rocm-swplat" revision="37742ce15b76b44e4b271c1e66d13d2fa7bd003e" />
     <project name="RCP" remote="gpuopen-tools" revision="3a49405a1500067c49d181844ec90aea606055bb" />
-    <!-- gdb projects -->
+<!-- gdb projects -->
     <project name="ROCgdb" remote="rocm-devtools" />
     <project name="ROCdbgapi" remote="rocm-devtools" />
-    <!-- ROCm Libraries -->
+<!-- ROCm Libraries -->
+    <project name="rdc" remote="roc-github" />
     <project name="rocBLAS" remote="rocm-swplat" />
+    <project name="Tensile" remote="rocm-swplat" />
     <project name="hipBLAS" remote="rocm-swplat" />
     <project name="rocFFT" remote="rocm-swplat" />
+    <project name="hipFFT" remote="rocm-swplat" />
     <project name="rocRAND" remote="rocm-swplat" />
     <project name="rocSPARSE" remote="rocm-swplat" />
     <project name="rocSOLVER" remote="rocm-swplat" />
@@ -61,19 +64,11 @@
     <project name="rocThrust" remote="rocm-swplat" />
     <project name="hipCUB" remote="rocm-swplat" />
     <project name="rocPRIM" remote="rocm-swplat" />
-    <project name="AMDMIGraphX" remote="rocm-swplat" revision="e66968a25f9342a28af1157b06cbdbf8579c5519" />
+    <project name="hipfort" remote="rocm-swplat" />
+    <project name="AMDMIGraphX" remote="rocm-swplat" />
     <project name="ROCmValidationSuite" remote="rocm-devtools" />
-    <!-- Projects for AOMP -->
-    <project name="ROCT-Thunk-Interface" path="aomp/roct-thunk-interface" remote="roc-github" />
-    <project name="ROCR-Runtime" path="aomp/rocr-runtime" remote="roc-github" />
-    <project name="ROCm-Device-Libs" path="aomp/rocm-device-libs" remote="roc-github" />
-    <project name="ROCm-CompilerSupport" path="aomp/rocm-compilersupport" remote="roc-github" />
-    <project name="rocminfo" path="aomp/rocminfo" remote="roc-github" />
-    <project name="HIP" path="aomp/hip-on-vdi" remote="rocm-devtools" />
-    <project name="aomp" path="aomp/aomp" remote="rocm-devtools" />
-    <project name="aomp-extras" path="aomp/aomp-extras" remote="rocm-devtools" />
-    <project name="flang" path="aomp/flang" remote="rocm-devtools" />
-    <project name="amd-llvm-project" path="aomp/amd-llvm-project" remote="rocm-devtools" />
-    <project name="ROCclr" path="aomp/vdi" remote="rocm-devtools" />
-    <project name="ROCm-OpenCL-Runtime" path="aomp/opencl-on-vdi" remote="roc-github" />
+<!-- Projects for OpenMP-Extras -->
+    <project name="aomp" path="openmp-extras/aomp" remote="rocm-devtools" />
+    <project name="aomp-extras" path="openmp-extras/aomp-extras" remote="rocm-devtools" />
+    <project name="flang" path="openmp-extras/flang" remote="rocm-devtools" />
 </manifest>

images/test.rst

@@ -0,0 +1 @@
+

version_history.md

@@ -1,503 +0,0 @@
-## ROCm Version History
-This file contains archived version history information for the [ROCm project](https://github.com/RadeonOpenCompute/ROCm)
-
-### Current ROCm Version: 3.3
-- [New features and enhancements in ROCm v3.1](#new-features-and-enhancements-in-rocm-v31)
-- [New features and enhancements in ROCm v3.0](#new-features-and-enhancements-in-rocm-v30)
-- [New features and enhancements in ROCm v2.10](#new-features-and-enhancements-in-rocm-v210)
-- [New features and enhancements in ROCm 2.9](#new-features-and-enhancements-in-rocm-29)
-- [New features and enhancements in ROCm 2.8](#new-features-and-enhancements-in-rocm-28)
-- [New features and enhancements in ROCm 2.7.2](#new-features-and-enhancements-in-rocm-272)
-- [New features and enhancements in ROCm 2.7](#new-features-and-enhancements-in-rocm-27)
-- [New features and enhancements in ROCm 2.6](#new-features-and-enhancements-in-rocm-26)
-- [New features and enhancements in ROCm 2.5](#new-features-and-enhancements-in-rocm-25)
-- [New features and enhancements in ROCm 2.4](#new-features-and-enhancements-in-rocm-24)
-- [New features and enhancements in ROCm 2.3](#new-features-and-enhancements-in-rocm-23)
-- [New features and enhancements in ROCm 2.2](#new-features-and-enhancements-in-rocm-22)
-- [New features and enhancements in ROCm 2.1](#new-features-and-enhancements-in-rocm-21)
-- [New features and enhancements in ROCm 2.0](#new-features-and-enhancements-in-rocm-20)
-- [New features and enhancements in ROCm 1.9.2](#new-features-and-enhancements-in-rocm-192)
-- [New features and enhancements in ROCm 1.9.2](#new-features-and-enhancements-in-rocm-192-1)
-- [New features and enhancements in ROCm 1.9.1](#new-features-and-enhancements-in-rocm-191)
-- [New features and enhancements in ROCm 1.9.0](#new-features-and-enhancements-in-rocm-190)
-- [New features as of ROCm 1.8.3](#new-features-as-of-rocm-183)
-- [New features as of ROCm 1.8](#new-features-as-of-rocm-18)
-- [New Features as of ROCm 1.7](#new-features-as-of-rocm-17)
-- [New Features as of ROCm 1.5](#new-features-as-of-rocm-15)
-
-
-## New features and enhancements in ROCm v3.2
-The AMD ROCm v3.2 release was not productized.
-
-## New features and enhancements in ROCm v3.1
-### Change in ROCm Installation Directory Structure
-
-A fresh installation of the ROCm toolkit installs the packages in the /opt/rocm-<version> folder. Previously, ROCm toolkit packages were installed in the /opt/rocm folder.
-
-### Reliability, Accessibility, and Serviceability Support for Vega 7nm
-
-The Reliability, Accessibility, and Serviceability (RAS) support for Vega7nm is now available.
-
-### SLURM Support for AMD GPU
-
-SLURM (Simple Linux Utility for Resource Management) is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for large and small Linux clusters.
-
-
-## New features and enhancements in ROCm v3.0
-### Support for CentOS RHEL v7.7 <a id="centos-anchor"></a> 
-Support is extended for CentOS/RHEL v7.7 in the ROCm v3.0 release. For more information about the CentOS/RHEL v7.7 release, see:
-
-[CentOS/RHEL](https://centos.org/forums/viewtopic.php?t=71657)
-
-
-### Initial distribution of AOMP 0.7-5 in ROCm v3.0 <a id="aomp-anchor"></a> 
-The code base for this release of AOMP is the Clang/LLVM 9.0 sources as of October 8th, 2019. The LLVM-project branch used to build this release is AOMP-191008. It is now locked. With this release, an artifact tarball of the entire source tree is created. This tree includes a Makefile in the root directory used to build AOMP from the release tarball. You can use Spack to build AOMP from this source tarball or build manually without Spack.
-
-For more information about AOMP 0.7-5, see: [AOMP](https://github.com/ROCm-Developer-Tools/aomp/tree/roc-3.0.0)
-
-
-### Fast Fourier Transform Updates
-The Fast Fourier Transform (FFT) is an efficient algorithm for computing the Discrete Fourier Transform. Fast Fourier transforms are used in signal processing, image processing, and many other areas. The following real FFT performance change is made in the ROCm v3.0 release:
-
-•	Implement efficient real/complex 2D transforms for even lengths.
-
-Other improvements:
-
-•	More 2D test coverage sizes.
-
-•	Fix buffer allocation error for large 1D transforms.
-
-•	C++ compatibility improvements.
-
-### MemCopy Enhancement for rocProf
-In the v3.0 release, the rocProf tool is enhanced with an additional capability to dump asynchronous GPU memcopy information into a .csv file. You can use the '-hsa-trace' option to create the results_mcopy.csv file.
-Future enhancements will include column labels.
-
-
-### New features and enhancements in ROCm v2.10
-#### rocBLAS Support for Complex GEMM
-The rocBLAS library is a gpu-accelerated implementation of the standard Basic Linear Algebra Subroutines (BLAS). rocBLAS is designed to enable you to develop algorithms, including high performance computing, image analysis, and machine learning.
-
-In the AMD ROCm release v2.10, support is extended to the General Matrix Multiply (GEMM) routine for multiple small matrices processed simultaneously for rocBLAS in AMD Radeon Instinct MI50. Both single and double precision, CGEMM and ZGEMM, are now supported in rocBLAS.
-
-#### Support for SLES 15 SP1
-In the AMD ROCm v2.10 release, support is added for SUSE Linux® Enterprise Server (SLES) 15 SP1. SLES is a modular operating system for both multimodal and traditional IT.
-
-#### Code Marker Support for rocProfiler and rocTracer Libraries
-Code markers provide the external correlation ID for the calling thread. This function indicates that the calling thread is entering and leaving an external API region.
-
-### New features and enhancements in ROCm 2.9
-
-#### Initial release for Radeon Augmentation Library(RALI)
-The AMD Radeon Augmentation Library (RALI) is designed to efficiently decode and process images from a variety of storage formats and modify them through a processing graph programmable by the user. RALI currently provides C API.
-
-#### Quantization in MIGraphX v0.4
-MIGraphX 0.4 introduces support for fp16 and int8 quantization. For additional details, as well as other new MIGraphX features, see [MIGraphX documentation](https://github.com/ROCmSoftwarePlatform/AMDMIGraphX/wiki/Getting-started:-using-the-new-features-of-MIGraphX-0.4).
-
-#### rocSparse csrgemm
-csrgemm enables the user to perform matrix-matrix multiplication with two sparse matrices in CSR format.
-
-#### Singularity Support
-ROCm 2.9 adds support for Singularity container version 2.5.2.
-
-#### Initial release of rocTX
-ROCm 2.9 introduces rocTX, which provides a C API for code markup for performance profiling.  This initial release of rocTX supports annotation of code ranges and ASCII markers.  For an example, see this [code](https://github.com/ROCm-Developer-Tools/roctracer/blob/amd-master/test/MatrixTranspose_test/MatrixTranspose.cpp).
-
-#### Added support for Ubuntu 18.04.3
-Ubuntu 18.04.3 is now supported in ROCm 2.9.
-
-
-
-### New features and enhancements in ROCm 2.8
-
-#### Support for NCCL2.4.8 API
-Implements ncclCommAbort() and ncclCommGetAsyncError() to match the NCCL 2.4.x API
-
-### New features and enhancements in ROCm 2.7.2
-
-This release is a hotfix for ROCm release 2.7.
-
-#### Issues fixed in ROCm 2.7.2
-
-##### A defect in upgrades from older ROCm releases has been fixed.
-
-##### rocprofiler --hiptrace and --hsatrace fails to load roctracer library
-In ROCm 2.7.2, rocprofiler --hiptrace and --hsatrace fails to load roctracer library defect has been fixed.  
-To generate traces, please provide directory path also using the parameter: -d <$directoryPath> for example:
-```shell
-/opt/rocm/bin/rocprof  --hsa-trace -d $PWD/traces /opt/rocm/hip/samples/0_Intro/bit_extract/bit_extract
-  ```
-All traces and results will be saved under $PWD/traces path
-
-#### Upgrading from ROCm 2.7 to 2.7.2
-
-To upgrade, please remove 2.7 completely as specified [for ubuntu](#how-to-uninstall-from-ubuntu-1604-or-Ubuntu-1804) or [for centos/rhel](#how-to-uninstall-rocm-from-centosrhel-76), and install 2.7.2 as per instructions [install instructions](#installing-from-amd-rocm-repositories)
-
-#### Other notes
-
-  To use rocprofiler features, the following steps need to be completed before using rocprofiler:
-
-  ##### Step-1: Install roctracer
-
-###### Ubuntu 16.04 or Ubuntu 18.04:
-
-  ```shell
-  sudo apt install roctracer-dev
-  ```
-
-######  CentOS/RHEL 7.6:
-
-  ```shell
-  sudo yum install roctracer-dev
-  ```
-  ##### Step-2: Add /opt/rocm/roctracer/lib to LD_LIBRARY_PATH
-  
-### New features and enhancements in ROCm 2.7
-
-#### [rocFFT] Real FFT Functional
-Improved real/complex 1D even-length transforms of unit stride. Performance improvements of up to 4.5x are observed. Large problem sizes should see approximately 2x.
-
-#### rocRand Enhancements and Optimizations
-- Added support for new datatypes: uchar, ushort, half.
-- Improved performance on "Vega 7nm" chips, such as on the Radeon Instinct MI50
-- mtgp32 uniform double performance changes due generation algorithm standardization. Better quality random numbers now generated with 30% decrease in performance
-- Up to 5% performance improvements for other algorithms
-
-#### RAS
-Added support for RAS on Radeon Instinct MI50, including:
-- Memory error detection
-- Memory error detection counter
-
-#### ROCm-SMI enhancements
-Added ROCm-SMI CLI and LIB support for FW version, compute running processes, utilization rates, utilization counter, link error counter, and unique ID.
-
-### New features and enhancements in ROCm 2.6
-
-#### ROCmInfo enhancements
-ROCmInfo was extended to do the following:
-For ROCr API call errors including initialization determine if the error could be explained by:
-- ROCk (driver) is not loaded / available
-- User does not have membership in appropriate group - "video"
-- If not above print the error string that is mapped to the returned error code
-- If no error string is available, print the error code in hex
-
-#### Thrust - Functional Support on Vega20
-ROCm2.6 contains the first official release of rocThrust and hipCUB. rocThrust is a port of thrust, a parallel algorithm library. hipCUB is a port of CUB, a reusable software component library. Thrust/CUB has been ported to the HIP/ROCm platform to use the rocPRIM library. The HIP ported library works on HIP/ROCm platforms.
-
-Note: rocThrust and hipCUB library replaces https://github.com/ROCmSoftwarePlatform/thrust (hip-thrust), i.e. hip-thrust has been separated into two libraries, rocThrust and hipCUB. Existing hip-thrust users are encouraged to port their code to rocThrust and/or hipCUB. Hip-thrust will be removed from official distribution later this year.
-
-#### MIGraphX v0.3
-MIGraphX optimizer adds support to read models frozen from Tensorflow framework. Further details and an example usage at https://github.com/ROCmSoftwarePlatform/AMDMIGraphX/wiki/Getting-started:-using-the-new-features-of-MIGraphX-0.3
-
-#### MIOpen 2.0
-- This release contains several new features including an immediate mode for selecting convolutions, bfloat16 support, new layers, modes, and algorithms.
-- MIOpenDriver, a tool for benchmarking and developing kernels is now shipped with MIOpen.
-BFloat16 now supported in HIP requires an updated rocBLAS as a GEMM backend.
-- Immediate mode API now provides the ability to quickly obtain a convolution kernel.
-- MIOpen now contains HIP source kernels and implements the ImplicitGEMM kernels. This is a new feature and is currently disabled by default. Use the environmental variable "MIOPEN_DEBUG_CONV_IMPLICIT_GEMM=1" to activation this feature. ImplicitGEMM requires an up to date HIP version of at least 1.5.9211.
-- A new "loss" catagory of layers has been added, of which, CTC loss is the first. See the API reference for more details.
-2.0 is the last release of active support for gfx803 architectures. In future releases, MIOpen will not actively debug and develop new features specifically for gfx803.
-- System Find-Db in memory cache is disabled by default. Please see build instructions to enable this feature.
-Additional documentation can be found here: https://rocmsoftwareplatform.github.io/MIOpen/doc/html/
-
-#### Bloat16 software support in rocBLAS/Tensile
-Added mixed precision bfloat16/IEEE f32 to gemm_ex. The input and output matrices are bfloat16. All arithmetic is in IEEE f32.
-
-#### AMD Infinity Fabric™ Link enablement
-The ability to connect four Radeon Instinct MI60 or Radeon Instinct MI50 boards in two hives or two Radeon Instinct MI60 or Radeon Instinct MI50 boards in four hives via AMD Infinity Fabric™ Link GPU interconnect technology has been added.
-
-#### ROCm-smi features and bug fixes
-  - mGPU & Vendor check
-  - Fix clock printout if DPM is disabled
-  - Fix finding marketing info on CentOS
-  - Clarify some error messages
-
-#### ROCm-smi-lib enhancements
-- Documentation updates
-- Improvements to *name_get functions
-
-#### RCCL2 Enablement
-RCCL2 supports collectives intranode communication using PCIe, Infinity Fabric™, and pinned host memory, as well as internode communication using Ethernet (TCP/IP sockets) and Infiniband/RoCE (Infiniband Verbs).  Note: For Infiniband/RoCE, RDMA is not currently supported.
-
-#### rocFFT enhancements
-- Added: Debian package with FFT test, benchmark, and sample programs
-- Improved: hipFFT interfaces
-- Improved: rocFFT CPU reference code, plan generation code and logging code
-
-### New features and enhancements in ROCm 2.5
-
-#### UCX 1.6 support
-Support for UCX version 1.6 has been added.
-
-#### BFloat16 GEMM in rocBLAS/Tensile
-Software support for BFloat16 on Radeon Instinct MI50, MI60 has been added.  This includes:
-- Mixed precision GEMM with BFloat16 input and output matrices, and all arithmetic in IEEE32 bit
-- Input matrix values are converted from BFloat16 to IEEE32 bit, all arithmetic and accumulation is IEEE32 bit. Output values are rounded from IEEE32 bit to BFloat16
-- Accuracy should be correct to 0.5 ULP
-
-#### ROCm-SMI enhancements
-CLI support for querying the memory size, driver version, and firmware version has been added to ROCm-smi.
-
-#### [PyTorch] multi-GPU functional support (CPU aggregation/Data Parallel)
-Multi-GPU support is enabled in PyTorch using Dataparallel path for versions of PyTorch built using the 06c8aa7a3bbd91cda2fd6255ec82aad21fa1c0d5 commit or later.
-
-#### rocSparse optimization on Radeon Instinct MI50 and MI60
-This release includes performance optimizations for csrsv routines in the rocSparse library.
-
-#### [Thrust] Preview
-Preview release for early adopters. rocThrust is a port of thrust, a parallel algorithm library. Thrust has been ported to the HIP/ROCm platform to use the rocPRIM library. The HIP ported library works on HIP/ROCm platforms.
-
-Note: This library will replace https://github.com/ROCmSoftwarePlatform/thrust in a future release. The package for rocThrust (this library) currently conflicts with version 2.5 package of thrust. They should not be installed together.
-
-#### Support overlapping kernel execution in same HIP stream
-HIP API has been enhanced to allow independent kernels to run in parallel on the same stream.
-
-#### AMD Infinity Fabric&#x2122; Link enablement
-The ability to connect four Radeon Instinct MI60 or Radeon Instinct MI50 boards in one hive via AMD Infinity Fabric™ Link GPU interconnect technology has been added.
-### New features and enhancements in ROCm 2.4
-
-#### TensorFlow 2.0 support
-ROCm 2.4 includes the enhanced compilation toolchain and a set of bug fixes to support TensorFlow 2.0 features natively
-
-#### AMD Infinity Fabric&#x2122; Link enablement
-ROCm 2.4 adds support to connect two Radeon Instinct MI60 or Radeon Instinct MI50 boards via AMD Infinity Fabric&#x2122; Link GPU interconnect technology.
-
-### New features and enhancements in ROCm 2.3
-
-#### Mem usage per GPU
-Per GPU memory usage is added to rocm-smi.
-Display information regarding used/total bytes for VRAM, visible VRAM and GTT, via the --showmeminfo flag
-
-#### MIVisionX, v1.1 - ONNX
-ONNX parser changes to adjust to new file formats
-
-#### MIGraphX, v0.2
-MIGraphX 0.2 supports the following new features:
-* New Python API
-* Support for additional ONNX operators and fixes that now enable a large set of Imagenet models
-* Support for RNN Operators
-* Support for multi-stream Execution
-* [Experimental] Support for Tensorflow frozen protobuf files
-
-See: [Getting-started:-using-the-new-features-of-MIGraphX-0.2](https://github.com/ROCmSoftwarePlatform/AMDMIGraphX/wiki/Getting-started:-using-the-new-features-of-MIGraphX-0.2) for more details
-
-#### MIOpen, v1.8 - 3d convolutions and int8
-* This release contains full 3-D convolution support and int8 support for inference.
-* Additionally, there are major updates in the performance database for major models including those found in Torchvision.
-
-See: [MIOpen releases](https://github.com/ROCmSoftwarePlatform/MIOpen/releases)
-
-#### Caffe2 -  mGPU support
-Multi-gpu support is enabled for Caffe2.
-
-#### rocTracer library, ROCm tracing API for collecting runtimes API and asynchronous GPU activity traces
-HIP/HCC domains support is introduced in rocTracer library.
-
-#### BLAS -  Int8 GEMM performance, Int8 functional and performance
-Introduces support and performance optimizations for Int8 GEMM, implements TRSV support, and includes improvements and optimizations with Tensile.
-
-#### Prioritized L1/L2/L3 BLAS (functional)
-Functional implementation of BLAS L1/L2/L3 functions
-
-#### BLAS - tensile optimization
-Improvements and optimizations with tensile
-
-#### MIOpen Int8 support
-Support for int8
-
-### New features and enhancements in ROCm 2.2
-
-#### rocSparse Optimization on Vega20
-Cache usage optimizations for csrsv (sparse triangular solve), coomv
-(SpMV in COO format) and ellmv (SpMV in ELL format) are available.
-
-#### DGEMM and DTRSM Optimization
-Improved DGEMM performance for reduced matrix sizes (k=384, k=256)
-
-#### Caffe2
-Added support for multi-GPU training
-
-### New features and enhancements in ROCm 2.1
-
-#### RocTracer v1.0 preview release – 'rocprof' HSA runtime tracing and statistics support -
-Supports HSA API tracing and HSA asynchronous GPU activity including kernels execution and memory copy
-
-#### Improvements to ROCM-SMI tool -
-Added support to show real-time PCIe bandwidth usage via the -b/--showbw flag
-
-#### DGEMM Optimizations -
-Improved DGEMM performance for large square and reduced matrix sizes (k=384, k=256)
-
-### New features and enhancements in ROCm 2.0
-
-#### Adds support for RHEL 7.6 / CentOS 7.6 and Ubuntu 18.04.1
-
-#### Adds support for Vega 7nm, Polaris 12 GPUs
-
-#### Introduces MIVisionX
-* A comprehensive computer vision and machine intelligence libraries, utilities and applications bundled into a single toolkit.
-
-#### Improvements to ROCm Libraries
-* rocSPARSE & hipSPARSE
-* rocBLAS with improved DGEMM efficiency on Vega 7nm
-
-#### MIOpen
-* This release contains general bug fixes and an updated performance database
-* Group convolutions backwards weights performance has been improved
-* RNNs now support fp16
-
-#### Tensorflow multi-gpu and Tensorflow FP16 support for Vega 7nm
-* TensorFlow v1.12 is enabled with fp16 support
-
-#### PyTorch/Caffe2 with Vega 7nm Support
-* fp16 support is enabled
-* Several bug fixes and performance enhancements
-* Known Issue: breaking changes are introduced in ROCm 2.0 which are not addressed upstream yet. Meanwhile, please continue to use ROCm fork at https://github.com/ROCmSoftwarePlatform/pytorch
-
-#### Improvements to ROCProfiler tool
-* Support for Vega 7nm
-
-#### Support for hipStreamCreateWithPriority
-* Creates a stream with the specified priority. It creates a stream on which enqueued kernels have a different priority for execution compared to kernels enqueued on normal priority streams. The priority could be higher or lower than normal priority streams.
-
-#### OpenCL 2.0 support
-* ROCm 2.0 introduces full support for kernels written in the OpenCL 2.0 C language on certain devices and systems.  Applications can detect this support by calling the “clGetDeviceInfo” query function with “parame_name” argument set to “CL_DEVICE_OPENCL_C_VERSION”.  In order to make use of OpenCL 2.0 C language features, the application must include the option “-cl-std=CL2.0” in options passed to the runtime API calls responsible for compiling or building device programs.  The complete specification for the OpenCL 2.0 C language can be obtained using the following link: https://www.khronos.org/registry/OpenCL/specs/opencl-2.0-openclc.pdf
-
-#### Improved Virtual Addressing (48 bit VA) management for Vega 10 and later GPUs
-* Fixes Clang AddressSanitizer and potentially other 3rd-party memory debugging tools with ROCm
-* Small performance improvement on workloads that do a lot of memory management
-* Removes virtual address space limitations on systems with more VRAM than system memory
-
-#### Kubernetes support
-
-### New features and enhancements in ROCm 1.9.2
-#### RDMA(MPI) support on Vega 7nm
-* Support ROCnRDMA based on Mellanox InfiniBand
-
-#### Improvements to HCC
-* Improved link time optimization
-
-#### Improvements to ROCProfiler tool
-* General bug fixes and implemented versioning APIs
-
-### New features and enhancements in ROCm 1.9.2
-#### RDMA(MPI) support on Vega 7nm
-* Support ROCnRDMA based on Mellanox InfiniBand
-
-#### Improvements to HCC
-* Improved link time optimization
-
-#### Improvements to ROCProfiler tool
-* General bug fixes and implemented versioning APIs
-
-#### Critical bug fixes
-
-### New features and enhancements in ROCm 1.9.1
-#### Added DPM support to Vega 7nm
-* Dynamic Power Management feature is enabled on Vega 7nm.
-
-#### Fix for 'ROCm profiling' that used to fail with a “Version mismatch between HSA runtime and libhsa-runtime-tools64.so.1” error
-
-### New features and enhancements in ROCm 1.9.0
-
-#### Preview for Vega 7nm
-* Enables developer preview support for Vega 7nm
-
-#### System Management Interface
-* Adds support for the ROCm SMI (System Management Interface) library, which provides monitoring and management capabilities for AMD GPUs.
-
-#### Improvements to HIP/HCC
-* Support for gfx906
-* Added deprecation warning for C++AMP.  This will be the last version of HCC supporting C++AMP.
-* Improved optimization for global address space pointers passing into a GPU kernel
-* Fixed several race conditions in the HCC runtime
-* Performance tuning to the unpinned copy engine
-* Several codegen enhancement fixes in the compiler backend
-
-#### Preview for rocprof Profiling Tool
-Developer preview (alpha) of profiling tool rocProfiler. It includes a command-line front-end, `rpl_run.sh`, which enables:
-* Cmd-line tool for dumping public per kernel perf-counters/metrics and kernel timestamps
-* Input file with counters list and kernels selecting parameters
-* Multiple counters groups and app runs supported
-* Output results in CSV format
-
-The tool can be installed from the `rocprofiler-dev` package. It will be installed into: `/opt/rocm/bin/rpl_run.sh`
-
-#### Preview for rocr Debug Agent rocr_debug_agent
-The ROCr Debug Agent is a library that can be loaded by ROCm Platform Runtime to provide the following functionality:
-* Print the state for wavefronts that report memory violation or upon executing a "s_trap 2" instruction.
-* Allows SIGINT (`ctrl c`) or SIGTERM (`kill -15`) to print wavefront state of aborted GPU dispatches.
-* It is enabled on Vega10 GPUs on ROCm1.9.
-
-The ROCm1.9 release will install the ROCr Debug Agent library at `/opt/rocm/lib/librocr_debug_agent64.so`
-
-
-#### New distribution support
-
-* Binary package support for Ubuntu 18.04
-
-#### ROCm 1.9 is ABI compatible with KFD in upstream Linux kernels.
-Upstream Linux kernels support the following GPUs in these releases:
-4.17: Fiji, Polaris 10, Polaris 11
-4.18: Fiji, Polaris 10, Polaris 11, Vega10
-
-Some ROCm features are not available in the upstream KFD:
-* More system memory available to ROCm applications
-* Interoperability between graphics and compute
-* RDMA
-* IPC
-
-To try ROCm with an upstream kernel, install ROCm as normal, but do not install the rock-dkms package. Also add a udev rule to control `/dev/kfd` permissions:
-
-```
-    echo 'SUBSYSTEM=="kfd", KERNEL=="kfd", TAG+="uaccess", GROUP="video"' | sudo tee /etc/udev/rules.d/70-kfd.rules
-```
-
-### New features as of ROCm 1.8.3
-
-* ROCm 1.8.3 is a minor update meant to fix compatibility issues on Ubuntu releases running kernel 4.15.0-33
-
-### New features as of ROCm 1.8
-
-#### DKMS driver installation
-
- * Debian packages are provided for DKMS on Ubuntu
- * RPM packages are provided for CentOS/RHEL 7.4 and 7.5 support
- * See the [ROCT-Thunk-Interface](https://github.com/RadeonOpenCompute/ROCT-Thunk-Interface/tree/roc-1.8.x) and [ROCK-Kernel-Driver](https://github.com/RadeonOpenCompute/ROCK-Kernel-Driver/tree/roc-1.8.x) for additional documentation on driver setup
-
-#### New distribution support
-
- * Binary package support for Ubuntu 16.04 and 18.04
- * Binary package support for CentOS 7.4 and 7.5
- * Binary package support for RHEL 7.4 and 7.5
-
-#### Improved OpenMPI via UCX support
-
- * UCX support for OpenMPI
- * ROCm RDMA
-
-### New Features as of ROCm 1.7
-
-#### DKMS driver installation
-
- * New driver installation uses Dynamic Kernel Module Support (DKMS)
- * Only amdkfd and amdgpu kernel modules are installed to support AMD hardware
- * Currently only Debian packages are provided for DKMS (no Fedora suport available)
- * See the [ROCT-Thunk-Interface](https://github.com/RadeonOpenCompute/ROCT-Thunk-Interface/tree/roc-1.7.x) and [ROCK-Kernel-Driver](https://github.com/RadeonOpenCompute/ROCK-Kernel-Driver/tree/roc-1.7.x) for additional documentation on driver setup
-
-### New Features as of ROCm 1.5
-
-#### Developer preview of the new OpenCL 1.2 compatible language runtime and compiler
-
- * OpenCL 2.0 compatible kernel language support with OpenCL 1.2 compatible
-   runtime
- * Supports offline ahead of time compilation today;
-   during the Beta phase we will add in-process/in-memory compilation.
-
-#### Binary Package support for Ubuntu 16.04
-
-#### Binary Package support for Fedora 24 is not currently available
-
-#### Dropping binary package support for Ubuntu 14.04, Fedora 23
-
-#### IPC support