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A combination of both. This work targets multicore, but execution on the GPU is definitely possible. It's just a different line of research. I'd highly recommen
by shwestrick 5y ago
A combination of both. This work targets multicore, but execution on the GPU is definitely possible. It's just a different line of research. I'd highly recommend taking a look at Futhark (https://futhark-lang.org/ https://futhark-lang.org/), which has a similar programming model (purely functional and parallel), but targets GPU. The compilation strategy is quite a bit different!
- joe_the_user 5y agoI have looked Futhark, however... What I find more interesting is things like Dyna-Soar[1] as well as the parent project/paper. Futhark seems primarily very tensor-type computation specific (like APL+ extra features) and I'm interested in things that more naturally prone to code and data divergence and in trying to find ways to compensate for this. [1] https://2019.ecoop.org/details/ecoop-2019-papers/12/DynaSOAr-A-Parallel-Memory-Allocator-for-Object-oriented-Programming-on-GPUs-with-Ef https://2019.ecoop.org/details/ecoop-2019-papers/12/DynaSOAr...