Sparse matrix-matrix multiplication (SpMM) is a crucial kernel in various applications, including sparse deep neural networks [1]–[6], graph analytics [7], triangle counting [8], and linear algebra ...
Abstract: Matrix-vector multiplication is practically used in all Digital Signal Processing (DSP) algorithms. Particularly, in the channel emulation field, it is required to perform this algorithm in ...
MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat instead of electricity. These tiny structures could someday enable more ...
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