HARP: Hardware-Based Pseudo-Tiling for Sparse Matrix Multiplication Accelerator
JinKwon Kim, Myeongjae Jang, H.K. Nam, Soontae Kim
Abstract
General sparse matrix-matrix multiplication (SpGEMM) is a memory-bound workload, due to the compression format used. To minimize data movements for input matrices, outer product accelerators have been proposed. Since these accelerators access input matrices only once and then generate numerous partial products, managing the generated partial products is the key optimization factor. To reduce the number of partial products handled, the state-of-the-art accelerator uses software to tile an input matrix. However, the software-based tiling has three limitations. First, a user manually executes the tiling software and manages the tiles. Second, generating a compression format for each tile incurs memory-intensive operations. Third, an accelerator that uses the compression format cannot skip ineffectual accesses for input matrices.