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But are they the most efficient in cost-per-computation? For all the major data crunchers I'm familiar with, doing either finance or scientific calculations, th
by solve 11y ago
But are they the most efficient in cost-per-computation? For all the major data crunchers I'm familiar with, doing either finance or scientific calculations, that's the only metric they cared about.
Only place I can see the cost-per-computation metric not mattering is in space satellites. Am I way off?
- skaevola 11y agoFor any sort of mobile device energy-usage per computation is an important metric. Hence you have chips with multiple low power modes which can trade off different amounts of computational power with different amounts of power efficiency.
- solve 11y agoBut ASIC is 100x better than FPGA for energy per computation. Know of any mobile devices that have FPGAs on them now?
- _yosefk 11y agoIt's not fair to compare a programmable circuit with a fixed-function circuit though, because programmability is often a requirement.
- skaevola 11y agoSure: http://www.eejournal.com/archives/articles/20131118-lattice/ http://www.eejournal.com/archives/articles/20131118-lattice/ But you're right - when programmability isn't important you'd rather have an ASIC.
- _yosefk 11y agoDo you get more throughput per dollar with FPGA relative to GPUs? Most certainly, except for floating point stuff, especially double precision. (Finance would care much less than scientific computing and I think FPGAs are way more prominent there.)
- solve 11y agoYou sure? The ones I'm personally familiar with are investment banks that have hundreds of thousands of computers doing machine learning modeling. They ran the costs, and found GPUs to be far more cost effective.
- _yosefk 11y agoMachine learning software will tend to use floating point, hence the result IMO. In HFT for instance I'd expect things to be the opposite.