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>Acceleration is needed for training -- not running the models themselves This isn't true. Running neural networks (including CNNs) can be computationally and
by rm999 10y ago
>Acceleration is needed for training -- not running the models themselves
This isn't true. Running neural networks (including CNNs) can be computationally and power intensive, and lends itself to the vector operations of GPUs, FPGAs, and ASICs. Putting the computations on devoted hardware could enable embedded applications that simply aren't possible otherwise.
Here's a whitepaper by Microsoft about using FPGA's to speed up CNNs: http://research.microsoft.com/apps/pubs/?id=240715 http://research.microsoft.com/apps/pubs/?id=240715
Article by Google explaining the importance of optimizing neural networks to run on mobile phones: http://googleresearch.blogspot.com/2015/07/how-google-translate-squeezes-deep.html http://googleresearch.blogspot.com/2015/07/how-google-transl...
- zxv 10y agoAre there any good examples of FPGA implementations of CNN? I see one example in Verilog on github: https://github.com/ziyan/altera-de2-ann/blob/master/src/ann/ann.vhd https://github.com/ziyan/altera-de2-ann/blob/master/src/ann/...
- dharma1 10y agoRNN - http://arxiv.org/abs/1511.05552v4 http://arxiv.org/abs/1511.05552v4
- tacos 10y agoThe Google article specifically says they were able to solve the problem on the (tiny) CPU in the phone by using vector operations on the CPU. Again, this is a tiny doodad for power-starved devices that lack any micro. Have you played with Apple Accelerate? They've been baking this stuff into their chips for quite some time. Apple's FFT outperforms FFTW. https://developer.apple.com/library/mac/navigation/#section=Frameworks&topic=Accelerate https://developer.apple.com/library/mac/navigation/#section=...