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Even less if you use AMD GPU's -https://www.reddit.com/r/linux/comments/2zgpj8/15000_nvidia_...

I wonder why the popular deep learning frameworks are using mainly CUDA instead of OpenCL. Is because of better Linux GPU drivers? Wondering why AMD isn't jumping on deep learning

The Altera FP capable FPGA's sound real interesting too. 10 TFLOPS, OpenCL support?

http://www.slideshare.net/embeddedvision/a04-altera-singh

Looks like they're about to be bought by Intel? http://www.electronicsweekly.com/news/business/altera-import...

Does this mean FPGA co-processors in the future from Intel?



I would love to see AMD jump in the ring, and there's even an OpenCL port of Caffe in progress: https://github.com/BVLC/caffe/pull/2610

But its performance is less than half that of a GTX 980 running CUDA. Still, AMD is silly not to try and improve on this IMO.


Wonder what's causing the perf drop. Would make sense to Intel to push openCL for deep learning too


Bad compilers would be my guess. And not only would it make sense for Intel to push OpenCL for Deep Learning, but it would make sense (IMO of course) for them to push OpenCL as a much better abstraction for accessing the vector units in all their CPUs in a multicore fashion across the board.




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