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We talk power, not servers, at work because it’s the limiting resource at any scale. “How many MWatts do you need next year”. Its not that you can’t do these wo
by pstoll 4y ago
We talk power, not servers, at work because it’s the limiting resource at any scale. “How many MWatts do you need next year”. Its not that you can’t do these workloads on CPUs or GPUs - you can. But you can do it at 10x-30x less power on custom silicon.
That’s why Amazon did Graviton3; Google did TPUs and VPUs. Ditto on personal computer with Apple & M1/M2.
- fezfight 4y agoYou skipped over the entire smart phone era.
- pstoll 4y agoSure - add the Apple A chips; Qualcomm chips for communications, etc…
- sthreeaway 4y agoAn important caveat is that this is practically and theoretically true for "embarrassingly parallel" (in the term-of-art, not perjorative sense) compute problems, and only if one sets aside supply-chain issues. It's theoretically (but rarely practically) true for network-bound problems of all sorts. It's not theoretically (and usually not practically) true for storage-bound problems. (Though Wh/bytes-at-rest is a useful bounding metric to understand if you're trying to build a storage business. It's never zero if the integrity of a byte at rest is at all important. Integrity is complicated.) But in any case, supply chain issues tend to dominate as the limiting factor at the largest scale in my experience. This has always been true, even since before the current clusterfuck. Source: no comment.