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Just recently read the interview transcript [0] of CEO and CTO (Jim Keller) of Tenstorrent which I believe they're in the same field. That's interestingly deep

• dragontamer 5y ago
  These "AI processors" are just matrix-multiplication engines, often 8-bit or 16-bits. Maybe 4-bit in some cases. 16-bit (and smaller) just isn't enough for most compute problems. But emphasis on "most". Neural Nets clearly are fine with 16-bit, but some video game lighting effects can be calculated on 16-bit and look "good enough". Maybe a certified Jewelry Appraiser can tell the difference between 1.3 refractive index vs 1.35, but the typical video game player (and dare I say, human) won't be able to tell the difference. If all the light bounces are just slightly off, as long as its "close enough", you probably have good-enough looking ray-tracing or whatever. -------- I've also heard of "iterative solvers" being accelerated by 16-bit and 32-bit passes before doing a 64-bit pass. That's not applicable to all math problems of course, but that's still a methodology where your 16-bit performance accelerates your 64-bit ultimate answer.
  • lostmsu 5y ago
    For casual readers, the trend in neural nets has changed a bit, and for training TensorFloat-32 is gaining popularity: https://blogs.nvidia.com/blog/2020/05/14/tensorfloat-32-precision-format/ https://blogs.nvidia.com/blog/2020/05/14/tensorfloat-32-prec... Pure f16 overflows/underflows in many scenarios