5 ms·
FPGAs are not measuring up to GPUs yet for these tasks. There's too much floating-point math (and yes, Altera is addressing this) for forward prediction, and w
by varelse 11y ago
FPGAs are not measuring up to GPUs yet for these tasks. There's too much floating-point math (and yes, Altera is addressing this) for forward prediction, and way too much intermediate state to save for training (GPU memory controllers are 'da bomb for this). Finally, OpenCL compilation time on FPGAs is measured in hours as compared to seconds for GPUs.
That said, address all of the above and maybe NVIDIA's stock won't hit 50 next year.
- Sanddancer 11y agoThere are a few people that seem to be working with integer-based deep learning and FPGAs, and even though they're at the beginning of research, things are looking pretty promising. Here's a paper that was released earlier this year that seems to show that at least some algorithms can see a big benefit from FPGAs http://arxiv.org/pdf/1502.02551v1.pdf http://arxiv.org/pdf/1502.02551v1.pdf .
- dharma1 11y agodid you see this? http://arxiv.org/pdf/1510.03009v1.pdf http://arxiv.org/pdf/1510.03009v1.pdf
- nickpsecurity 11y agoNow THAT has some potential. Both for FPGA's and SIMD/MIMD architectures. Thanks for the link.