llvm
rust-gpu
llvm | rust-gpu | |
---|---|---|
10 | 82 | |
1,166 | 6,972 | |
3.9% | 1.1% | |
10.0 | 7.7 | |
6 days ago | 9 days ago | |
Rust | ||
GNU General Public License v3.0 or later | Apache License 2.0 |
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.
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
rust-gpu
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Vcc – The Vulkan Clang Compiler
Sounds cool, but this requires yet another language to learn[0]. As someone who only has limited knowledge in this space, could someone tell me how comparable is the compute functionality of rust-gpu[1], where I can just write rust?
[0] https://github.com/Hugobros3/shady#language-syntax
[1] https://github.com/EmbarkStudios/rust-gpu
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Candle: Torch Replacement in Rust
I don't do anything related to data science, but I feel like doing it in Rust would be nice.
You get operator overloading, so you can have ergonomic matrix operations that are typed also. Processing data on the CPU is fast, and crates like https://github.com/EmbarkStudios/rust-gpu make it very ergonomic to leverage the GPU.
I like this library for creating typed coordinate spaces for graphics programming (https://github.com/servo/euclid), I imagine something similar could be done to create refined types for matrices so you don't do matrix multiplication matrices of invalid sizes
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What's the coolest Rust project you've seen that made you go, 'Wow, I didn't know Rust could do that!'?
Do you mean rust-gpu?
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How a Nerdsnipe Led to a Fast Implementation of Game of Life
And https://github.com/EmbarkStudios/rust-gpu/tree/main/examples with the wgpu runner (here it runs the compute shader)
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What is Rust's potential in game development?
I don't know how major they are considered, but Embark Studios is doing quite a bit of Rust in the open source space, most notably (IMO) rust-gpu and kajiya
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[rust-gpu] How do I run/build my own shaders locally?
The examples in the rust-gpu repository are a good place to start
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Posh: Type-Safe Graphics Programming in Rust
There's another project that's similar that's being used by an actual game company: https://github.com/EmbarkStudios/rust-gpu
They see specific advantages here that would outweigh that negative. It's not my space (I play games, but know next to nothing about graphics programming), but there's at least one argument in the other direction.
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Introducing posh: Type-Safe Graphics Programming in Rust
Could this approach work for compute shaders (GPGPU) as well? So far, I think https://github.com/EmbarkStudios/rust-gpu is the state of the art in that area, but it adds a specific Rust compiler backend for generating SPIR-V rather than leaving that up to the driver. That seems more complicated than it needs to be... but maybe it has advantages too? Thoughts?
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Looking for high level GPU computing crate
https://github.com/embarkstudios/rust-gpu Allows you to create shaders (kernals) in Rust.
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With what languages are video games like League of Legends (most likely) programmed?
Also Embark Studios (formers DICE people) is doing a lot of work with Rust, all open source like Rust GPU https://github.com/EmbarkStudios/rust-gpu
What are some alternatives?
pocl - pocl - Portable Computing Language
llama.cpp - LLM inference in C/C++
oneTBB - oneAPI Threading Building Blocks (oneTBB)
wgpu - A cross-platform, safe, pure-Rust graphics API.
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!
Rust-CUDA - Ecosystem of libraries and tools for writing and executing fast GPU code fully in Rust.
meson - The Meson Build System
onnxruntime-rs - Rust wrapper for Microsoft's ONNX Runtime (version 1.8)
OCL-SDK
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.
featuresupport
DiligentEngine - A modern cross-platform low-level graphics library and rendering framework