Are you implying there are no use cases for matrix multiply?
In any case, the two main deep learning packages have already been updated so for the place this change was almost certainly targeted for, your complaint is answered. I'm just stunned that anyone would complain about hardware matrix multiplication? I've wondered why that hasn't been ubiquitous for the past 20 years.
Everyone should make that improvement in their hardware. Everyone should get rid of code implementing matrix mult and make the hardware call instead. It's common sense. Not to put too fine a point on it, but your complaint assumes that GeekBench is based on code that has implemented all those changes.
In any case, the two main deep learning packages have already been updated so for the place this change was almost certainly targeted for, your complaint is answered. I'm just stunned that anyone would complain about hardware matrix multiplication? I've wondered why that hasn't been ubiquitous for the past 20 years.
Everyone should make that improvement in their hardware. Everyone should get rid of code implementing matrix mult and make the hardware call instead. It's common sense. Not to put too fine a point on it, but your complaint assumes that GeekBench is based on code that has implemented all those changes.