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What else besides deep learning can the tensor core do well ?

• krona 9y ago
  multiplying and adding matrices are fairly fundamental operations. Here is a starting point: https://en.wikipedia.org/wiki/Multiply%E2%80%93accumulate_operation https://en.wikipedia.org/wiki/Multiply%E2%80%93accumulate_op...
  • science404 9y ago
    Yes but they are limited in size and in precision to FP16, which is not sufficient for most applications, especially scientific computing... What this person is asking I think is: Can you actually think of another concrete application?
• thearn4 9y ago
  CFD and other high-fidelity multiphysics simulations can be efficient when GPU-bound. It all comes down to being able to write a matrix and stream a bunch of vectors to multiply it by. When considering Krylov subspace methods, this extends to covering a large part of the problem space of linear algebra. I think the Tesla cards in particular are double precision, which is not necessarily the best for deep learning applications.
  • tanderson92 9y ago
    High-fidelity multiphysics seems incompatible with FP16, unless you're talking some kind of mixed precision method.