DASP

DASP: Specific Dense Matrix Multiply-Accumulate Units Accelerated General Sparse Matrix-Vector Multiplication

Sparse matrix-vector multiplication (SpMV) plays a key role in computational science and engineering, graph processing and machine learning applications. In this work, we propose DASP, a new algorithm using specific dense MMA units for accelerating the compute part of general SpMV. We analyze the row-wise distribution of nonzeros and group the rows into three categories containing long, medium and short rows, respectively. We then organize them into small blocks of proper sizes to meet the requirement of MMA computation. For the three categories, DASP offers different strategies to complete SpMV by efficiently utilizing the MMA units.