We’re liberating highly-optimized GPU kernels for an underexplored magnificence of neural community architectures: networks with block-sparse weights. Relying at the selected sparsity, those kernels can run orders of magnitude quicker than cuBLAS or cuSPARSE. We’ve used them to score cutting-edge leads to textual content sentiment research and generative modeling of textual content and photographs.
