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TL;DR Microsoft uses FPGAs. Google uses ASICs. MapD uses GPUs. FPGAs are more flexible. ASICs are faster. I think the FPGA approach is generally more usef
by CalChris 10y ago
TL;DR
Microsoft uses FPGAs. Google uses ASICs. MapD uses GPUs.
FPGAs are more flexible. ASICs are faster.
I think the FPGA approach is generally more useful and will trickle out into the marketplace. Indeed they are already available. So this article is more about Microsoft's fabric.
https://www.mrcy.com/products/ensemble-fcn8213-server-class-fpga-processing-blade-advancedtca/
It's not impossible to think this would make its way into an Azure cloud product. That won't happen with ASICs. But Google will clearly have an advantage on the problems they focus on.
- DannyBee 10y agoIf that's the TL;DR, it don't make a lot of sense. Microsoft/Google/whoever is going to use what makes the most sense for a given set of applications/etc they have, whether it's CPU's, GPU's, FPGA's, ASIC's, or massive armies of intelligent pigeons. I'm not sure why one would think all of them don't do all of them :) (in fact, i'd pretty much guarantee it)
- mycall 10y ago> I think the FPGA approach is generally more usefu Intel agrees with its purchase of Altera.
- Cyph0n 10y agoFPGAs are already powering key parts of both Azure and Bing. I asked Doug Burger after his presentation two weeks back at my university, and he said that currently the fabric is not reconfigurable. In other words, hardware acceleration is not available to customers yet, but it looks like they're working towards that. A nice little tidbit from the talk. They were able to translate all of Wikipedia from English to Russian using 90% of the deployed FPGAs in 0.1 seconds.