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I’m excited to announce the preprint of our paper “Bringing #UMAP Closer to the Speed of Light with #GPU Acceleration” is now available on Arxiv! Special thanks to all the co-authors @viclafargue1, @teju85, @EdwardRaffML, @oatesbag, @zstats @datametrician for making it possible.
This paper describes many design tricks, as well as core principals we followed, to accelerate #UMAP in @rapidsai #cuML and achieve SOA performance. Many of these tricks have been used to accelerate other algorithms in the #GPU computing ecosystem.
This paper was a team effort, and would not have been possible without such a wonderful group of co-authors. I’m very happy with how it turned out.
