3 ms·
Some people do, but they're by far the minority. CUDA / cuDNN are well tuned and integrated with the most popular libraries. At this point, in order to get pe
by madenine 10y ago
Some people do, but they're by far the minority.
CUDA / cuDNN are well tuned and integrated with the most popular libraries.
At this point, in order to get people to switch not only would your hardware have to be faster, but your replacement for cuDNN would have to be better as well. Which is by no means impossible, just difficult.
- x0x0 10y agoI disagree; most people use caffe / keras / theano / tensorflow / etc hiding the cuDNN details so end users won't care much. Offering more performance / shorter training loops is a big deal. Your typical ML learning loop with an expensive human regularly waiting for experiment results shows clear benefits.
- ogrisel 10y agoThe point is that there is no optimized cuDNN equivalent for AMD hardware at this point.
- deleted 10y ago[deleted]
- eightysixfour 10y agoAMD has built this middleware for all of those applications (keras, tensorflow, caffe, etc) and they show the performance results in their slides.
- deleted 10y ago[deleted]