clspv
llvm
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clspv | llvm | |
---|---|---|
8 | 10 | |
575 | 1,164 | |
2.3% | 5.5% | |
8.9 | 10.0 | |
4 days ago | 2 days ago | |
LLVM | ||
Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
clspv
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Vcc – The Vulkan Clang Compiler
See https://github.com/google/clspv for an OpenCL implementation on Vulkan Compute. There are plenty of quirks involved because the two standards use different varieties of SPIR-V ("kernels" vs. "shaders") and provide different guarantees (Vulkan Compute doesn't care much about numerical accuracy). The Mesa folks are also looking into this as part of their RustiCL (a modern OpenCL implementation) and Zink (implementing OpenGL and perhaps OpenCL itself on Vulkan) projects.
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AMD's CDNA 3 Compute Architecture
Vulkan Compute backends for numerical compute (as typified by both OpenCL and SYCL) are challenging, you can look at Google's cspv https://github.com/google/clspv project for the nitty gritty details. The lowest-effort path is actually via some combination of Rocm (for hardware that AMD bothers to support themselves) and the Mesa project's Rusticl backend (for everything else).
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WSL with CUDA Support
D3D12 has more compute features than Vulkan has. It works out for DXVK because games often don’t use those, but it’ll cause much more issues with CLon12.
By the way, if you are ready to have a _limited_ implementation without a full feature set because of Vulkan API limitations, clvk is a thing. The list of limitations of that approach is at https://github.com/google/clspv/blob/master/docs/OpenCLCOnVu...
tldr: Vulkan and OpenCL SPIR-V dialects are different, and the former has significant limitations affecting this use case
- Resources for Vulkan GPGPU searched
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Low overhead C++ interface for Apple's Metal API
For OpenCL on DX12, the test suite doesn't pass yet. Every Khronos OpenCL 1.2 CTS test passes on at least one hardware driver, but there's none that pass them all. That is why CLon12 isn't submitted to Khronos's compliant products list yet.
The pointer semantics that Vulkan has aren't very amenable to implementing a compliant OpenCL implementation on top of. There are also some other limitatons: https://github.com/google/clspv/blob/master/docs/OpenCLCOnVu....
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[Hardware Unboxed] - Apple M1 Pro Review - Is It Really Faster than Intel/AMD?
Vulkan is much more limited, notably because of Vulkan's SPIR-V dialect limitations. That makes a compliant OpenCL 1.2 impl on top of Vulkan impossible. (see: https://github.com/google/clspv/blob/master/docs/OpenCLCOnVulkan.md)
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Cross Platform GPU-Capable Framework?
OpenCL really is your best bet for a cross-platform GPU-capable framework. OpenCL 3.0 cleared out a lot of the cruft from OpenCL 2.x so it's seeing a lot more adoption. The most cross-platform solution is still OpenCL 1.2, largely for MacOS, but OpenCL 3.0 is becoming more and more common for Windows and Linux and multiple devices. Even on platforms without native OpenCL support there are compatibility layers that implement OpenCL on top of DirectX (OpenCLOn12) or Vulkan (clvk and clspv).
llvm
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Vcc – The Vulkan Clang Compiler
Intel's modern compilers (icx, icpx) are clang-based. There is an open-source version [1], and the closed-source version is built atop of this with extra closed-source special sauce.
AOCC and ROCm are also based on LLVM/clang.
[1] https://github.com/intel/llvm
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device::aspects ?
You are not missing anything spec-wise, it is just that particular version of the compiler/runtime doesn't support that query. Support for it was added in intel/llvm#7937 and it should be available in the next oneAPI release.
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How to install OpenCL for AMD CPU?
Install the Intel OpenCL CPU Runtime. AMD CPUs are x86-64 too, so they work just like Intel CPUs do. Afaik, performance is significantly better than with POCL. This also works with EPYC, like the new 96-core Genoa.
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Modern Software Development Tools and oneAPI Part 2
The Meson build system Version: 1.0.0 Source dir: /var/home/sri/Projects/simple-oneapi Build dir: /var/home/sri/Projects/simple-oneapi/builddir Build type: native build Project name: simple-oneapi Project version: 0.1.0 C compiler for the host machine: clang (clang 16.0.0 "clang version 16.0.0 (https://github.com/intel/llvm 08be083e07b1fd6437267e26adb92f1b647d57dd)") C linker for the host machine: clang ld.bfd 2.34 C++ compiler for the host machine: clang++ (clang 16.0.0 "clang version 16.0.0 (https://github.com/intel/llvm 08be083e07b1fd6437267e26adb92f1b647d57dd)") C++ linker for the host machine: clang++ ld.bfd 2.34 Host machine cpu family: x86_64 Host machine cpu: x86_64 Build targets in project: 1 Found ninja-1.11.1.git.kitware.jobserver-1 at /var/home/sri/.local/bin/ninja
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Modern Software Development Tools and oneAPI Part 1
$ sudo mkdir -p /opt/intel $ sudo mkdir -p /etc/OpenCL/vendors/intel_fpgaemu.icd $ cd /tmp $ wget https://github.com/intel/llvm/releases/download/2022-WW50/oclcpuexp-2022.15.12.0.01_rel.tar.gz $ wget https://github.com/intel/llvm/releases/download/2022-WW50/fpgaemu-2022.15.12.0.01_rel.tar.gz $ sudo bash # cd /opt/intel # mkdir oclfpgaemu- # cd oclfpgaemu- # tar xvfpz /tmp/fpgaemu-2022.15.12.0.01_rel.tar.gz # cd .. # mkdir oclcpuexp_ # cd oclcpuexp- # tar xvfpz /tmp/oclcpuexp- # cd ..
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Cross Platform Computing Framework?
oneAPI includes an implementation of SYCL called DPC++. This implementation supports Intel, Nvidia and AMD GPUs (currently for Nvidia and AMD you need to build the support from the source) but oneAPI also includes some libraries too like oneDNN and oneMKL that use SYCL.
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Does an actually general purpose GPGPU solution exist?
Yes, you can use multiple backends with the same compiled binary. For example you can use DPC++ with Nvidia, AMD and Intel GPU at the same time. ComputeCpp also has the ability to output a binary that can target multiple targets. Each backend generates the ISA for each GPU, and then the SYCL runtime chooses the right one at execution time. There is no ODR violation because each GPU executable is stored on separate ELF sections and loaded at runtime : the C++ linker does not see them. The code doesn't need to have any layers, the only changes you might (but don't have to) make are to optimize for specific processor features.
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Why Does SYCL Have Different Implementations, and What Version to Use for GPGPU Computing(With Slower CPU Mode for Testing/No Gpu Machines)?
Intel LLVM SYCL oneAPI DPC++ - an open source implementation of SYCL that is being contributed to the LLVM project
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How to set up Intel oneAPI?
I'm using intel cpu, and after reading this i'm just curious can i set this up with portage? Are there any ebuilds to build this? Do i need whole toolchain from intel site (3Gb+) or just 300 mb tar from their github?
- Benchmarking Division and Libdivide on Apple M1 and Intel AVX512
What are some alternatives?
OpenCLOn12 - The OpenCL-on-D3D12 mapping layer
pocl - pocl - Portable Computing Language
kompute - General purpose GPU compute framework built on Vulkan to support 1000s of cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usecases. Backed by the Linux Foundation.
oneTBB - oneAPI Threading Building Blocks (oneTBB)
GLSL - GLSL Shading Language Issue Tracker
AdaptiveCpp - Implementation of SYCL and C++ standard parallelism for CPUs and GPUs from all vendors: The independent, community-driven compiler for C++-based heterogeneous programming models. Lets applications adapt themselves to all the hardware in the system - even at runtime!
alpaka - Abstraction Library for Parallel Kernel Acceleration :llama:
meson - The Meson Build System
MoltenVK - MoltenVK is a Vulkan Portability implementation. It layers a subset of the high-performance, industry-standard Vulkan graphics and compute API over Apple's Metal graphics framework, enabling Vulkan applications to run on macOS, iOS and tvOS.
OCL-SDK
SPIRV-VM - Virtual machine for executing SPIR-V
featuresupport