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The Tensor cores will be great for machine learning and the FP32/FP64 fantastic for HPC, but I'd be surprised if there were a lot of applications using both of
by fancyfredbot 5y ago
The Tensor cores will be great for machine learning and the FP32/FP64 fantastic for HPC, but I'd be surprised if there were a lot of applications using both of these features at once. I wonder if there's room for a competitor to come in and sell another huge accelerator but with only one of these two features either at a lower price or with more performance? Perhaps the power density would be too high if everything was in use at once?
- TheGuyWhoCodes 5y agoJust look at Cerebras Wafer-Scale Engine it's basically a chip the size of a Wafer but it's not cheap...
- nine_k 5y agoCan different tenant VMs access different parts of H100 in parallel? If so, it may be a reasonable mix.
- fancyfredbot 5y agoRight now no - the unit of subdivision for MIG is too coarse. Everyone gets the same proportion of each function
- throwawaygh 5y ago> room for a competitor to come in and sell another huge accelerator but with only one of these two features either at a lower price or with more performance? They'd need fab capacity first. I wouldn't count on it any time soon, and chip gens have short lives.
- JonChesterfield 5y agoGraphcore's IPU is a machine learning variant on that. Power density seems to be ok. The CTO's talks (used to, I'm out of date) talk about dark silicon a lot. I share your suspicion that fp64 and ML workloads are distinct but can see each running on the same cluster at different times.