3 ms·

I'm glad to see this is being studied. I did a brief half-semester project summarizing the usefulness of accelerators after the death of Dennard's law and Moore

I'm glad to see this is being studied. I did a brief half-semester project summarizing the usefulness of accelerators after the death of Dennard's law and Moore's law (this was when Intel was still pushing out incremental improvements on 14nm). The short summary is that accelerators offered substantial performance per watt improvement, at the cost of longer development timelines, cost of manufacturing in the case of ASICs and ASIPs, and the inability to fit large algorithms on FPGAs. Though Microsoft found a way to daisy-chain FPGAs for Bing's page rank, it just didn't produce the order-of-magnitude improvement necessary to justify moving to FPGAs. With smaller algorithms or bigger FPGAs or occasional operation offloading (like what we do now with TPUs and GPUs), they could be good candidates for accelerators. Of course the real killer is how easy it is(n't) to develop for them. AMD offers much better performance per dollar than Nvidia, but of course their poor drivers make using their hardware a fool's errand. RADs sound like a good idea. We should be making reprogrammable hardware available and easy to use for everyone.

15155 2y ago
> AMD offers much better performance per dollar than Nvidia, but of course their poor drivers make using their hardware a fool's errand. I would never use their IP or drivers, but Xilinx hardware is top notch. What drivers are you using? XRT?
buildbot 2y ago
Brainwave is/was very successful? Still serving your searches! (I work on one of the teams that came out of brainwave, not with them directly) https://www.microsoft.com/en-us/research/project/project-brainwave/ https://www.microsoft.com/en-us/research/project/project-bra... https://www.microsoft.com/en-us/research/publication/a-configurable-cloud-scale-dnn-processor-for-real-time-ai/ https://www.microsoft.com/en-us/research/publication/a-confi... https://www.microsoft.com/en-us/research/blog/a-microsoft-custom-data-type-for-efficient-inference/ https://www.microsoft.com/en-us/research/blog/a-microsoft-cu... -> This led to the OCP MX work: https://www.opencompute.org/blog/amd-arm-intel-meta-microsoft-nvidia-and-qualcomm-standardize-next-generation-narrow-precision-data-formats-for-ai https://www.opencompute.org/blog/amd-arm-intel-meta-microsof...

15155 2y ago

> AMD offers much better performance per dollar than Nvidia, but of course their poor drivers make using their hardware a fool's errand. I would never use their IP or drivers, but Xilinx hardware is top notch. What drivers are you using? XRT?

buildbot 2y ago

Brainwave is/was very successful? Still serving your searches! (I work on one of the teams that came out of brainwave, not with them directly) https://www.microsoft.com/en-us/research/project/project-brainwave/ https://www.microsoft.com/en-us/research/project/project-bra... https://www.microsoft.com/en-us/research/publication/a-configurable-cloud-scale-dnn-processor-for-real-time-ai/ https://www.microsoft.com/en-us/research/publication/a-confi... https://www.microsoft.com/en-us/research/blog/a-microsoft-custom-data-type-for-efficient-inference/ https://www.microsoft.com/en-us/research/blog/a-microsoft-cu... -> This led to the OCP MX work: https://www.opencompute.org/blog/amd-arm-intel-meta-microsoft-nvidia-and-qualcomm-standardize-next-generation-narrow-precision-data-formats-for-ai https://www.opencompute.org/blog/amd-arm-intel-meta-microsof...