C++ gpu-computing

Open-source C++ projects categorized as gpu-computing
Topics: GPU Gpgpu Opencl Cuda HPC

Top 23 C++ gpu-computing Projects

  • FluidX3D

    The fastest and most memory efficient lattice Boltzmann CFD software, running on all GPUs via OpenCL.

  • Project mention: FluidX3D | news.ycombinator.com | 2024-03-24
  • 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.

  • Project mention: Intel CEO: 'The entire industry is motivated to eliminate the CUDA market' | news.ycombinator.com | 2023-12-14

    The two I know of are IREE and Kompute[1]. I'm not sure how much momentum the latter has, I don't see it referenced much. There's also a growing body of work that uses Vulkan indirectly through WebGPU. This is currently lagging in performance due to lack of subgroups and cooperative matrix mult, but I see that gap closing. There I think wonnx[2] has the most momentum, but I am aware of other efforts.

    [1]: https://kompute.cc/

    [2]: https://github.com/webonnx/wonnx

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • MatX

    An efficient C++17 GPU numerical computing library with Python-like syntax

  • Project mention: An efficient C++17 GPU numerical computing library with Python-like syntax | /r/programming | 2023-10-05
  • stdgpu

    stdgpu: Efficient STL-like Data Structures on the GPU

  • 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!

  • Project mention: AdaptiveCpp | news.ycombinator.com | 2024-05-18
  • cccl

    CUDA C++ Core Libraries

  • Project mention: GDlog: A GPU-Accelerated Deductive Engine | news.ycombinator.com | 2023-12-03

    https://github.com/topics/datalog?l=rust ... Cozo, Crepe

    Crepe: https://github.com/ekzhang/crepe :

    > Crepe is a library that allows you to write declarative logic programs in Rust, with a Datalog-like syntax. It provides a procedural macro that generates efficient, safe code and interoperates seamlessly with Rust programs.

    Looks like there's not yet a Python grammar for the treeedb tree-sitter: https://github.com/langston-barrett/treeedb :

    > Generate Soufflé Datalog types, relations, and facts that represent ASTs from a variety of programming languages.

    Looks like roxi supports n3, which adds `=>` "implies" to the Turtle lightweight RDF representation: https://github.com/pbonte/roxi

    FWIW rdflib/owl-rl: https://owl-rl.readthedocs.io/en/latest/owlrl.html :

    > simple forward chaining rules are used to extend (recursively) the incoming graph with all triples that the rule sets permit (ie, the “deductive closure” of the graph is computed).

    ForwardChainingStore and BackwardChainingStore implementations w/ rdflib in Python: https://github.com/RDFLib/FuXi/issues/15

    Fast CUDA hashmaps

    Gdlog is built on CuCollections.

    GPU HashMap libs to benchmark: Warpcore, CuCollections,




    /? Rocm HashMap


  • cuda-api-wrappers

    Thin C++-flavored header-only wrappers for core CUDA APIs: Runtime, Driver, NVRTC, NVTX.

  • Project mention: VUDA: A Vulkan Implementation of CUDA | news.ycombinator.com | 2023-07-01

    1. This implements the clunky C-ish API; there's also the Modern-C++ API wrappers, with automatic error checking, RAII resource control etc.; see: https://github.com/eyalroz/cuda-api-wrappers (due disclosure: I'm the author)

    2. Implementing the _runtime_ API is not the right choice; it's important to implement the _driver_ API, otherwise you can't isolate contexts, dynamically add newly-compiled JIT kernels via modules etc.

    3. This is less than 3000 lines of code. Wrapping all of the core CUDA APIs (driver, runtime, NVTX, JIT compilation of CUDA-C++ and of PTX) took me > 14,000 LoC.

  • SaaSHub

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  • triSYCL

    Generic system-wide modern C++ for heterogeneous platforms with SYCL from Khronos Group

  • ginkgo

    Numerical linear algebra software package (by ginkgo-project)

  • AutoDock-GPU

    AutoDock for GPUs and other accelerators

  • Project mention: Is there any current way to do molecular docking in MacOS? | /r/chemistry | 2023-07-10
  • vuh

    Vulkan compute for people

  • clvk

    Implementation of OpenCL 3.0 on Vulkan

  • Gpufit

    GPU-accelerated Levenberg-Marquardt curve fitting in CUDA

  • OpenCL-Wrapper

    OpenCL is the most powerful programming language ever created. Yet the OpenCL C++ bindings are cumbersome and the code overhead prevents many people from getting started. I created this lightweight OpenCL-Wrapper to greatly simplify OpenCL software development with C++ while keeping functionality and performance.

  • Project mention: What 8x AMD Instinct MI200 GPUs can do with a combined 512GB VRAM: Bell 222 Helicopter in FluidX3D CFD - 10 Billion Cells, 75k Time Steps, 71TB vizualized - 6.4 hours compute+rendering with OpenCL | /r/pcmasterrace | 2023-06-24

    In case you go with OpenCL, start here: https://github.com/ProjectPhysX/OpenCL-Wrapper

  • beatmup

    Beatmup: image and signal processing library

  • dlprimitives

    Deep Learning Primitives and Mini-Framework for OpenCL

  • Project mention: Dlprimitives: Deep Learning Primitives and Mini-Framework for OpenCL | news.ycombinator.com | 2023-06-17
  • gpuowl

    GPU Mersenne primality test.

  • cuda_memtest

    Fork of CUDA GPU memtest :eyeglasses:

  • OpenCL-Benchmark

    A small OpenCL benchmark program to measure peak GPU/CPU performance.

  • dpctl

    Python SYCL bindings and SYCL-based Python Array API library

  • Project mention: Data Parallel Extensions for Python: near-native speed for scientific computing | news.ycombinator.com | 2023-11-24

    Considering how poorly it seems to support cuda as a backend [0], I wouldn't hold my breath about non intel vendor support (amd cpu or gpu). As for less common gpus, there really is no good support in any library. If you ever want to go down a fun rabbit hole, try to use the gpu in a raspberry pi for something. You'll eventually find one guy who reverse engineered the drivers to make a compiler but that's it.

    [0] https://github.com/IntelPython/dpctl/discussions/1124

  • ParallelReductionsBenchmark

    Thrust, CUB, TBB, AVX2, CUDA, OpenCL, OpenMP, SyCL - all it takes to sum a lot of numbers fast!

  • ALUs

    GPU accelerated earth observation data processors

  • OpenCL_Wrapper_By_PunalManalan

    Lightweight, Easy to use OpenCL Wrapper By Punal Manalan. 'OCLW_P::OpenCLWrapper' This Single line of code does Everything In a Compact And Easy to Manage Manner!. Use this code wherever and whenever you want to!

  • SaaSHub

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NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020).

C++ gpu-computing related posts


What are some of the best open-source gpu-computing projects in C++? This list will help you:

Project Stars
1 FluidX3D 3,268
2 kompute 1,512
3 MatX 1,120
4 stdgpu 1,092
5 AdaptiveCpp 1,053
6 cccl 832
7 cuda-api-wrappers 737
8 triSYCL 436
9 ginkgo 376
10 AutoDock-GPU 357
11 vuh 340
12 clvk 316
13 Gpufit 301
14 OpenCL-Wrapper 264
15 beatmup 191
16 dlprimitives 157
17 gpuowl 115
18 cuda_memtest 107
19 OpenCL-Benchmark 117
20 dpctl 96
21 ParallelReductionsBenchmark 60
22 ALUs 23
23 OpenCL_Wrapper_By_PunalManalan 3

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SaaSHub helps you find the best software and product alternatives