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Multiplatform Matrix Multiplication Kernels

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85 points homarp | 1 comments | 18 Jul 25 19:59 UTC | HN request time: 0.473s | source
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Lerc ◴[18 Jul 25 22:58 UTC] No.44610720[source]▶
Has there been much research into slightly flawed matrix multiplications?

If you have a measure of correctness, and a measure of performance. Is there a maximum value of correctness per some unit of processing that exists below a full matrix multiply

Obviously it can be done with precision, since that is what floating point is. But is there anything where you can save x% of computation and have fewer than x% incorrect values in a matrix multiplications?

Gradient descent wouldn't really care about a few (Reliably) dud values.

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1. MayeulC ◴[19 Jul 25 12:05 UTC] No.44614820[source]▶
Well, approximate computing seems to be a superset of the field you describe here, with many different approaches, including analog computation. As you say, some algorithms care a bit less about precision, especially for LSBs.