3 ms·
But not a petaflop @ 200W which is possible for deep learning. GPUs have driven a lot of progress in deep learning, I'll be excited to see what DPUs will do in
by deepnotderp 10y ago
But not a petaflop @ 200W which is possible for deep learning. GPUs have driven a lot of progress in deep learning, I'll be excited to see what DPUs will do in terms of deep learning progress, assuming of course, they have floating point, (otherwise creative algorithm will be a problem)
- jacquesm 10y agoCommercial deep learning ASICs will definitely happen. The Nvidia stuff is in a way getting there, to go from 3500 ops / tick to 35000 ops / tick with the same power consumption will most likely require more than a merely incremental improvement in the hardware. It would have to be: - less general - a smaller process node - possibly more than one chip on a board tightly coupled - specialized data types - very tight coupling between memory and computation (so maybe memory on the chip) - a slightly higher clock speed, say twice as high GPUs are much too general but if all the factors above can be realized a factor of 10 in a PCIe add-in card should be possible.