Lairv t1_ir7p0xt wrote
Reply to comment by neanderthal_math in [R] Discovering Faster Matrix Multiplication Algorithms With Reinforcement Learning by EducationalCicada
In the article they try 2 types of reward: minimizing the rank of the tensor decomposition (i.e. minimizing total number of multiplication), and minimizing the runtime of the algorithm on a given hardware (they tried with nvidia V100 and TPUv2)
The latter could be actually useful since their graphs shows that the algorithms discovered reach better performances than cuBLAS (Fig.5)
neanderthal_math t1_ir8pk44 wrote
Thank you. That’s pretty cool.
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