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jeffhammond avatar jeffhammond commented on September 26, 2024

DGEMM cannot and will not be performance portable unless your standards for performance are low. There are decades of empirical results confirming this.

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chsasank avatar chsasank commented on September 26, 2024

I think with a pinch of autotuning, I think it is possible. For example, see what triton does for matrix multiplication. No hard coding of important parameters and higher level abstraction. Nothing specific to Nvidia anymore.

If your definition of performance portability is the same binary and no hardware specific optimizations, I agree with you. But I guess, my definition of that is not dissimilar to BLIS's own version of it: https://github.com/flame/blis/tree/master/config

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nick-knight avatar nick-knight commented on September 26, 2024

my definition of that is not dissimilar to BLIS's own version of it: https://github.com/flame/blis/tree/master/config

We welcome your contributions of new configurations, to accompany the ones you've discovered in blis/config. And you are welcome to use autotuning to assist your (micro)kernel development.

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chsasank avatar chsasank commented on September 26, 2024

Unfortunately BLIS doesn't compile to any sort of GPU :(

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