Sparse-matrix dense-matrix multiplication (SpMM) is a fundamental linear algebra operation and a building block for more complex algorithms such as finding the solutions of linear systems, computing eigenvalues through the preconditioned conjugate gradient, and multiple right-hand sides Krylov subspace iterative solvers. SpMM is also an important kernel used in many domains such as fluid dynamics…
]]>Deep neural networks achieve outstanding performance in a variety of fields, such as computer vision, speech recognition, and natural language processing. The computational power needed to process these neural networks is rapidly increasing, so efficient models and computation are crucial. Neural network pruning, removing unnecessary model parameters to yield a sparse network, is a useful way to…
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