Why is the DGX-1 so expensive? Why is it needed?
I don't understand. A Titan-X has nearly 4,000 cuda cores. A DGX-1 V100 has about 40,000 cuda cores. A Titan-X costs about £1,000, a DGX-1 costs about £100,000. Are these things to limited by transfer rates between cards that the 10 fold increase is price per core is worth it? I thought in a neural net architecture you could process data on sets of layers independently and only needed to transfer data across the connections at the top and bottom layers of each set? I am genuinely puzzled. Can someone tell me if these nets work really differently to the multilayer back-prop I know of old and why the DGX-1 costs so much compared to the Titan-X?
Yours, an academic who did NN stuff in the 1980s and 90s using such parallel compute monsters as the 16 CPU Encore Multimax!