3 ms·
I'm aware. But it's not just about clock speed per se. AVX512 has some _very_ specialized instructions that are specifically designed to speed up matrix-matrix
by m0zg 8y ago
I'm aware. But it's not just about clock speed per se. AVX512 has some _very_ specialized instructions that are specifically designed to speed up matrix-matrix and matrix-vector multiply. Even at a significantly slower clock those instructions improve things by a lot if you do linear algebra. Most of linalg is done on GPUs nowadays, but not all of it.
- bitL 8y agoAs a consequence, TR/Ryzen is very slow in "classical" ML in Python (I can tell), because MKL/AVX2 seems to be way slower. This could be fixed with Zen 2; AVX512 then will be likely at 2/3 of Intel's performance without slowing down the rest of the system during computations.
- m0zg 8y agoI agree with this assessment. Frankly, GPUs are so much faster for dense linalg than even the highest end Intel (or AMD) chips that anything that can be done on GPUs should be done there. But that requires one to know how to work with them, if the primitives don't already exist, and most people are oblivious to the finer points.