5 ms·

Futhark 0.9.1 released – now with CUDA backend

72 points by Athas 8y ago

4thaccount 8y ago
Anyone use Futhark for genetic algorithms or other evolutionary computing uses yet?
- sevensor 8y ago
  I've done a lot of work with GAs, and in my experience the effort is better spent parallelizing the model rather than the evaluations. (You can use a fast model for lots of other stuff besides optimization.) However, if you already have a compact model that's fast to evaluate yet difficult to optimize, then you might have a good candidate for this approach.
  - 4thaccount 8y ago
    The problems I'm interested in have over 12k constraints and need to solve pretty fast. They're among the hardest MIP problems out there and I'd love to see how well a GA compares on a real model, but it will take me a long time to create a comparable GA model.
    - sevensor 8y ago
      12k constraints? Without a major change in formulation, you're almost certainly way better off with convex optimization. As long as the problem is convex, anyway.
pdimitar 8y ago
Interesting. I wonder if there's a curated list of languages that have GPU backends? I think it's high time for most mainstream languages to add GPUs to their concurrency / parallelism story.
- pjmlp 8y ago
  Out of my head, Haskell, Java, .NET, Rust, C, C++, Fortran, D, Julia.
  - nostrademons 8y ago
    So LLVM?
    - pjmlp 8y ago
      Actually SPIR and PTX, eventually OpenCL as well.
      - nostrademons 8y ago
        But is it a SPIR/PTX backend for LLVM (and any language that targets it), or is it a direct backend for Haskell/Rust/Java/C# and all the other implementations that you listed?
        pjmlp 8y ago
        It a mix of SPIR/PTX backends for LLVM and proprietary toolchains. Java, https://www.ibm.com/support/knowledgecenter/en/SSYKE2_8.0.0/com.ibm.java.80.doc/docs/gpu_developing_cuda4j.html https://www.ibm.com/support/knowledgecenter/en/SSYKE2_8.0.0/... http://www.jcuda.de/ http://www.jcuda.de/ https://clojurecuda.uncomplicate.org/ https://clojurecuda.uncomplicate.org/ Haskell Accelerate, http://www.acceleratehs.org/ http://www.acceleratehs.org/ Obsidian, https://github.com/svenssonjoel/Obsidian https://github.com/svenssonjoel/Obsidian .NET Hybridizer , http://www.altimesh.com/hybridizer-essentials/ http://www.altimesh.com/hybridizer-essentials/, Alea GPU, http://www.quantalea.com/ http://www.quantalea.com/ NMmath, https://www.centerspace.net/nmath-premium/ https://www.centerspace.net/nmath-premium/ D, DCompute, https://github.com/libmir/dcompute https://github.com/libmir/dcompute Julia, JuliaGPU, https://github.com/JuliaGPU https://github.com/JuliaGPU
- fulafel 8y ago
  What's the closest thing to a C implementation currently? Some languages implement at least subsets of it.
fenollp 8y ago
Points for helping against monopolies. I have been following the project for some years and am very happy to see it grow and on top of a functional front end at that! Now where is Futhark's GEMM implementation & the vs. CuDNN benchmarks?
- twtw 8y ago
  cuBLAS does GEMM.
olodus 8y ago
Had the wonderful opportunity to not only play around with Futhark last year but also have a lecture from Troels himself when I took a course in parallel functional programming last year. Really like the language and are really interested in what it could do in the future. When I used it last there were still a few kinks to work out to use it but from what I've seen from the releases lately more and more of them are being worked out. Love the direction it is going. Best of luck for the future of the project.

72 points by Athas 8y ago

4thaccount 8y ago

Anyone use Futhark for genetic algorithms or other evolutionary computing uses yet?

sevensor 8y ago
I've done a lot of work with GAs, and in my experience the effort is better spent parallelizing the model rather than the evaluations. (You can use a fast model for lots of other stuff besides optimization.) However, if you already have a compact model that's fast to evaluate yet difficult to optimize, then you might have a good candidate for this approach.
- 4thaccount 8y ago
  The problems I'm interested in have over 12k constraints and need to solve pretty fast. They're among the hardest MIP problems out there and I'd love to see how well a GA compares on a real model, but it will take me a long time to create a comparable GA model.
  - sevensor 8y ago
    12k constraints? Without a major change in formulation, you're almost certainly way better off with convex optimization. As long as the problem is convex, anyway.

pdimitar 8y ago

Interesting. I wonder if there's a curated list of languages that have GPU backends? I think it's high time for most mainstream languages to add GPUs to their concurrency / parallelism story.

pjmlp 8y ago
Out of my head, Haskell, Java, .NET, Rust, C, C++, Fortran, D, Julia.
- nostrademons 8y ago
  So LLVM?
  - pjmlp 8y ago
    Actually SPIR and PTX, eventually OpenCL as well.
    - nostrademons 8y ago
      But is it a SPIR/PTX backend for LLVM (and any language that targets it), or is it a direct backend for Haskell/Rust/Java/C# and all the other implementations that you listed?
      - pjmlp 8y ago
        It a mix of SPIR/PTX backends for LLVM and proprietary toolchains. Java, https://www.ibm.com/support/knowledgecenter/en/SSYKE2_8.0.0/com.ibm.java.80.doc/docs/gpu_developing_cuda4j.html https://www.ibm.com/support/knowledgecenter/en/SSYKE2_8.0.0/... http://www.jcuda.de/ http://www.jcuda.de/ https://clojurecuda.uncomplicate.org/ https://clojurecuda.uncomplicate.org/ Haskell Accelerate, http://www.acceleratehs.org/ http://www.acceleratehs.org/ Obsidian, https://github.com/svenssonjoel/Obsidian https://github.com/svenssonjoel/Obsidian .NET Hybridizer , http://www.altimesh.com/hybridizer-essentials/ http://www.altimesh.com/hybridizer-essentials/, Alea GPU, http://www.quantalea.com/ http://www.quantalea.com/ NMmath, https://www.centerspace.net/nmath-premium/ https://www.centerspace.net/nmath-premium/ D, DCompute, https://github.com/libmir/dcompute https://github.com/libmir/dcompute Julia, JuliaGPU, https://github.com/JuliaGPU https://github.com/JuliaGPU
fulafel 8y ago
What's the closest thing to a C implementation currently? Some languages implement at least subsets of it.

fenollp 8y ago

Points for helping against monopolies. I have been following the project for some years and am very happy to see it grow and on top of a functional front end at that! Now where is Futhark's GEMM implementation & the vs. CuDNN benchmarks?

twtw 8y ago
cuBLAS does GEMM.

olodus 8y ago

Had the wonderful opportunity to not only play around with Futhark last year but also have a lecture from Troels himself when I took a course in parallel functional programming last year. Really like the language and are really interested in what it could do in the future. When I used it last there were still a few kinks to work out to use it but from what I've seen from the releases lately more and more of them are being worked out. Love the direction it is going. Best of luck for the future of the project.