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Besides that hack, getting your head around the way to optimize code for a GPU takes a while. Then the real challenge is taking code that is based on random acc
by rocqua 4y ago
Besides that hack, getting your head around the way to optimize code for a GPU takes a while. Then the real challenge is taking code that is based on random access to gigabytes of RAM, and making that code work with any kind of performance on the GPU performance model.
There are cases where the random access to RAM are very deep in the algorithm. Consider e.g. sparse matrix multiplication.
- nobodyandproud 4y ago“optimal” is a different goalpost than “a lot faster”. Some easy-to-parallelize math and vector operations can yield impressive results without it being anywhere near optimal. I do agree that optimal requires mastery of GPU programming; but I also think GPU programming can yield good results without said mastery, and be quite accessible If anything it should be easier than writing raw multi-threading code, because GPUs aren’t (weren’t?) general purpose calculation units. So more bare metal concerns, but less to reason about overall.