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Computer science
Parallel computing
SIMD
Operand
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Memory architecture
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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
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).
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