BabelStream VS gpu-kernel-runner

Compare BabelStream vs gpu-kernel-runner and see what are their differences.

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BabelStream gpu-kernel-runner
1 1
311 18
2.9% -
7.7 6.7
3 days ago 5 days ago
C++ C++
GNU General Public License v3.0 or later BSD 3-clause "New" or "Revised" License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

BabelStream

Posts with mentions or reviews of BabelStream. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-21.
  • Fortran on GPU
    4 projects | /r/fortran | 21 Oct 2022
    I wrote the Fortran version of BabelStream (https://github.com/UoB-HPC/BabelStream/pull/135) to compare all of these, which might be useful as well. There is also MiniWeather, which supports all OpenMP, OpenACC and StdPar for GPU: https://github.com/mrnorman/miniWeather/tree/main/fortran.

gpu-kernel-runner

Posts with mentions or reviews of gpu-kernel-runner. We have used some of these posts to build our list of alternatives and similar projects.
  • How Jensen Huang's Nvidia Is Powering the A.I. Revolution
    1 project | news.ycombinator.com | 29 Nov 2023
    > but all the alternatives require significant redesign in languages and tools people are unfamiliar with and we can't afford that overhead

    Where I work, we've made it a principle to stay OpenCL-compatible even while going with NVIDIA due to their better-performing GPUs. I even go as far as writing kernels that can be compiled as either CUDA C++ or OpenCL-C, with a bit of duct-tape adapter headers:

    https://github.com/eyalroz/gpu-kernel-runner/blob/main/kerne...

    https://github.com/eyalroz/gpu-kernel-runner/blob/main/kerne...

    of course, if you're working with higher-level frameworks then it's more difficult, and you depend on whether or not they provided different backends. So, no thrust for AMD GPUs, for example, but pytorch and TensorFlow do let you use them.

What are some alternatives?

When comparing BabelStream and gpu-kernel-runner you can also consider the following projects:

nwchem-tce-triples-kernels - NWChem TCE CCSD(T) loop-driven kernels for performance optimization experiments

ArrayFire - ArrayFire: a general purpose GPU library.

bedrock-clump - A GPU accelerated program to search the minecraft world for the largest connected clump of layer 5 bedrock

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

miniWeather - A parallel programming training mini app simulating weather-like flows

alpaka - Abstraction Library for Parallel Kernel Acceleration :llama:

Kernels - This is a set of simple programs that can be used to explore the features of a parallel platform.

mixbench - A GPU benchmark tool for evaluating GPUs and CPUs on mixed operational intensity kernels (CUDA, OpenCL, HIP, SYCL, OpenMP)