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by kingvash 2889 days ago
Google really seems to be leading the pack with investments in silicon (e.g. TPU and recently announced edge tpu[1]). Other traditional silicon companies (Nvidia, Intel) seem to get it but I have yet to see investments from other tech companies (Amazon, FB, Netflix).

[1] https://techcrunch.com/2018/07/25/google-is-making-a-fast-sp...)
2 comments
zeusk 2889 days ago
Microsoft Research is pushing along as well, they just don't publicize it as much.

Azure has already deployed FPGAs (they believe, being able to deploy and make changes including changes to workload on the fly is more beneficial than the efficiency compared to using an ASIC) for networking and accelerated ML (Project Catapult and Project Brainwave).

tbh, I do agree with using FPGAs over ASICs given the speed at which the tech is moving. Google has already cycled through 3 versions of the TPU.

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ebikelaw 2889 days ago
The underlying operation of multiplying a shitload of numbers together hasn't changed at all. Google's revisions have essentially been more and way more multipliers, respectively.

The main problem with FPGAs is having to deal with the vendors and their evil tools. Those people have no idea what good software looks like, and no business being in my cloud. I guess if you're Microsoft and you already have demonstrated a 40-year history of having no taste in software then you'd be OK putting FPGA tooling into a datacenter. I personally wouldn't even execute that stuff in a sandbox, much less allow it to reprogram my platform.

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shaklee3 2888 days ago
Asic tools are very similar to fpga tools. You always simulate on fpga first before sending off the RTL for an asic.
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hollerith 2889 days ago
and yet all 3 versions of the TPU are ASICs, not FPGAs :)
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zeusk 2889 days ago
and? that only supports the argument of FPGAs over ASICs (unless Google is harboring some deep secret on cheap chip tapeout process).
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seanmcdirmid 2889 days ago
I heard that Google was actually late to the game on this, not realizing the value of GPUs over (just) distributed computing when the DNN trend started. Now they even have custom silicon...
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daviddumenil 2888 days ago
I think it was more a case that Google had a large existing investment in CPU-based compute.

A lot of Dean's initial work was getting models effectively training on that kind of hardware using distributed SGD.

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