To be practically useful, we don't need to beat vendors, just getting close would be enough, by the virtue of being open-source (and often portable). But I found, as an example, PETSc to be ~10x slower than MKL on CPU and CUDA on GPU; It still doesn't have native shared memory parallelism support on CPU etc.

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bee_rider 6 hours ago | parent [-]

Oh dang, thanks for the heads up. I was looking at them for the “next version” of my code.

The lack of a “blas/lapack/sparse equivalents that can dispatch to GPU or CPU” is really annoying. You’d think this would be somewhat “easy” (lol, nothing is easy), in the sense that we’ve got a bunch of big chunky operations…

	▲	shihab 5 hours ago \| parent [-]
		I should note PETSc is a big piece of software that does a lot of things. It also wraps many libraries, and those might ultimately dictate actual performance depending on what you plan on doing.