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DTSTART:19700308T020000
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DTSTAMP:20210402T160104Z
LOCATION:Track 3
DTSTART;TZID=America/New_York:20201119T110000
DTEND;TZID=America/New_York:20201119T113000
UID:submissions.supercomputing.org_SC20_sess156_pap506@linklings.com
SUMMARY:Efficient Tiled Sparse Matrix Multiplication through Matrix Signat
 ures
DESCRIPTION:Paper\n\nEfficient Tiled Sparse Matrix Multiplication through 
 Matrix Signatures\n\nKurt, Sukumaran-Rajam, Rastello, Sadayappan\n\nTiling
  is a key technique to reduce data movement in matrix computations. While 
 tiling is well understood and widely used for dense matrix/tensor computat
 ions, effective tiling of sparse matrix computations remains a challenging
  problem. This paper proposes a novel method to efficiently summarize the 
 impact of the sparsity structure of a matrix on achievable data reuse as a
  one-dimensional signature, which is then used to build an analytical cost
  model for tile size optimization for sparse matrix computations. The prop
 osed model-driven approach to sparse tiling is evaluated on two key sparse
  matrix kernels; Sparse Matrix-Matrix Multiplication (SpMM) and Sampled De
 nse Dense Matrix Multiplication (SDDMM). Experimental results demonstrate 
 that model-based tiled SpMM and SDDMM achieve high performance relative to
  the current state-of-the-art.\n\nTag: Algorithms, Graph Algorithms, Linea
 r Algebra\n\nRegistration Category: Tech Program Reg Pass
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