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cs.DC2024
High Performance Unstructured SpMM Computation Using Tensor Cores
Patrik Okanovic, Grzegorz Kwasniewski, Paolo Sylos Labini +3
High-performance sparse matrix-matrix (SpMM) multiplication is paramount for science and industry, as the ever-increasing sizes of data prohibit using dense data structures. Yet, e…
cs.DC2022★ 1 cited
Blocking Techniques for Sparse Matrix Multiplication on Tensor Accelerators
Paolo Sylos Labini, Massimo Bernaschi, Francesco Silvestri +1
Tensor accelerators have gained popularity because they provide a cheap and efficient solution for speeding up computational-expensive tasks in Deep Learning and, more recently, in…