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computer science parallel computing simd operand sparse matrix memory architecture computer hardware physics quantum mechanics gaussian

Marzieh Lenjani , Alif Ahmed , Mircea R. Stan , Kevin Skadron ·

YOU? · · 2022 · Open Access · · DOI: https://doi.org/10.1145/3470496.3527402 · OA: W4281621462

Processing-in-memory (PIM) minimizes data movement overheads by placing processing units near each memory segment. Recent PIMs employ processing units with a SIMD architecture. However, kernels with random accesses, such as sparse-matrix-dense-vector (SpMV) and sparse-matrix-sparse-vector (SpMSpV), cannot effectively exploit the parallelism of SIMD units because SIMD's ALUs remain idle until all the operands are collected from local memory segments (memory segment attached to the processing unit) or remote memory segments (other segments of the memory).