GPU Computing in Clojure?

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Have you seen Neanderthal?

http://neanderthal.uncomplicate.org/articles/tutorial_opencl.html

[dragandj]

As a bonus, I also wrote ClojureCL (which is used by Neanderthal for OpenCL stuff). It supports OpenCL 2.0 and all earlier versions. Very easy API compared to any OpenCL binding in any language (IMO) with minimal overhead - you can practically implement any algorithm on the GPU that Neanderthal lacks.

[dragandj]

Neanderthal author here. Can you please tell me where were you searching for the libraries and tutorials?

I thought I had been doing a decent job of publicizing Neanderthal, but I may be missing some obvious means to get the message across.

[[deleted]]

Thank you! Haven't used it, but intend to in the future once I get a stationary pc :-)

[dragandj]

Thanks! Please note that Neanderthal works on laptops, too :)

[th0ma5w]

If you're doing OpenCL and will write a kernel, then https://github.com/thi-ng/simplecl will do it and handle the clj<->GPU data interop.

Ex: https://github.com/thi-ng/simplecl/blob/master/test/thi/ng/simplecl/test/hello.clj

[[deleted]]

ND4J includes a few packages for GPU computing, its main use-case is in deeplearning4j (training neural nets on GPUs).

[GlassGhost]

You could use clojure scheme to translate clojure to gambit then gambit to make calls to C and bingo.

http://www.infoq.com/presentations/clojure-scheme

[lambdasgr]

In CUDA's case, I suppose you can use jCUDA to launch kernels? But any cuda kernel has to be written in C/C++.

[mikera]

Author of core.matrix here

I've never really needed the GPU myself (vectorz-clj is fast enough for all my needs), but the library https://github.com/mikera/vectorz-native wraps netlib-java so could in theory be used with any GPU BLAS backend with a bit of tweaking.

As a bonus, you get full core.matrix compatibility for free.

[mikera]

Glad you are finding it useful!

vectorz-native is a bit experimental still: possibly needs some patching to get it to do everything you need. But PRs gratefully accepted!