#Rocm vs opencl benchmark drivers#
#Rocm vs opencl benchmark driver#
#Rocm vs opencl benchmark full#
#Rocm vs opencl benchmark software#

The release of ROCm 5.1 is imminent, probably mid-February given a minor release each month. Within the main public meta-repository, there is an xml manifest for each official release: using git-repo, a version control tool built on top of git, is the recommended way to synchronize with the stack locally.

#Rocm vs opencl benchmark software#

ROCm software is currently spread across dozens of public GitHub repositories. Future integration with rocALUTION, rocSOLVER, MIOpen, and certain other ROCm libraries is planned. AMDGPU.jl uses ROCr's HSA implementation to upload native code onto the device and execute it, similar to how HIP loads its own generated device code.ĪMDGPU.jl also supports integration with ROCm's rocBLAS (for BLAS), rocRAND (for random number generation), and rocFFT (for FFTs). Instead of compiling code through HIP, AMDGPU.jl uses Julia's compiler to generate LLVM IR directly, which is later consumed by LLVM to generate native device code. Julia has the AMDGPU.jl package, which integrates with LLVM and selects components of the ROCm stack. Other acceleration & graphics interoperation Īs of version 3.0, Blender can now use HIP compute kernels for its renderer Cycles. Some related software is to be found at AMD Infinity hub. ROCm is used with the Exascale supercomputers ElCapitan and Frontier. ROCm is gaining significant traction in the top 500.

Iree (which uses LLVM Multi-Level Intermediate Representation (MLIR)).

Various Deep Learning frameworks have a ROCm backend: The main consumers of the stack are machine learning and high-performance computing/GPGPU applications.

#Rocm vs opencl benchmark drivers#

(on Linux: 1.1 (no Image support) with Mesa 3D, 2.0 with AMD drivers or AMD ROCm)ĪMD ROCm product manager gave a tour of the stack. The only consumer-grade GPU that has relatively equal support is, as of January 2022, the Radeon VII (GCN 5 - Vega).Ĭonsumer-grade GPUs Name of GPU seriesġ.2 (on Linux: 1.1 (no Image support) with Mesa 3D)

#Rocm vs opencl benchmark full#

See also: List of AMD graphics processing units Professional-grade GPUs ĪMD Instinct accelerators are the first-class ROCm citizens, alongside the prosumer Radeon Pro GPU series: they mostly see full support. Having ROCm functional there is involved. Īccelerated Processor Units (APU) are 'enabled', but not officially supported. RDNA2 is already 'enabled' but official support is planned for 2022.

The main micro-architectures where support is implemented are CDNA 1&2 (pro), RDNA 1&2 (consumer/prosumer), GCN 4th & 5th. ROCm is primarily targeted at discrete professional GPUs, but official support is wider, and extends to consumer-grade products. High-level programming HIP programming HIP(HCC) kernel language Memory allocation NUMA Heterogeneous Memory Model and Shared Virtual Memory ROCm code objects Compute/Graphics interop Low-level programming Hardware support One of the best technical introductions about the stack and ROCm/HIP programming, remains, to date, to be found on Reddit.

#Rocm vs opencl benchmark driver#

ROCm as a stack ranges from the kernel driver to the end-user applications.ĪMD has introductory videos about AMD GCN hardware, and ROCm programming via its learning portal. Microsoft AMP C++ 1.2 Programming abilities This approach was dropped for ROCm: now it builds only GPU code, using LLVM, and its AMDGPU backend that was upstreamed, although there is still research on such enhanced modularity with LLVM MLIR. HSA was aimed at producing a middle-level, hardware-agnostic intermediate representation, that could be JIT-compiled to the eventual hardware (GPU, FPGA.) using the appropriate finalizer. ROCm stack builds upon previous AMD GPU stacks, some tools trace back to GPUOpen, others to the Heterogeneous System Architecture (HSA). ROCm was launched around 2016 with the Boltzmann Initiative. The first GPGPU software stack from ATI/AMD was Close to Metal, which became Stream. 5.2.3 HIP - Heterogeneous Interface for Portability.4.2.3 Other acceleration & graphics interoperation.2.2.2.2 Heterogeneous Memory Model and Shared Virtual Memory.