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UID:submissions.supercomputing.org_SC25_sess535_drs114@linklings.com
SUMMARY:Accelerating Sparse Tensor Contractions
DESCRIPTION:Saurabh Raje (University of Utah)\n\nSparse tensor contraction
 s (SpTC) are a bottleneck for several algorithms in scientific computing, 
 data science, artificial intelligence and graphics. The SpTC operation is 
 any expression of the form R(l0,l1, r0) = X(l0, l1, c0) * Y(r0, c0) where 
 two tensors are multiplied along several dimensions to form a multidimensi
 onal result. Sparse tensor networks are an extension of this problem such 
 that there are more than two inputs. This thesis aims to accelerate both—t
 he SpTC primitive and sparse tensor networks with multiple SpTC terms. We 
 develop kernels and IR optimizations to improve code-generation for sparse
  tensor networks.\n\nTo generate efficient code for a sparse tensor networ
 k, several inter-dependent optimizations must be made on the intermediate 
 representation (IR). This includes sparse tensor mode order, and loop fusi
 on to reduce intermediate tensors. Correctness requirements impose constra
 ints on these variables.\n\nWe develop CoNST, a code-generator that co-opt
 imizes these variables. An integer constraint system is solved by the Z3 S
 MT solver and the result lowers to a unique fused loop structure and tenso
 r mode layouts for the entire contraction tree. CoNST outperforms state-of
 -the-art compilers by orders of magnitude in run-time.\n\nTo accelerate th
 e SpTC operation, we perform the first analysis of data-access costs and m
 emory requirements for loop orders. We develop FaSTCC, a hash-based parall
 el implementation of the SpTC operation that uses the fastest loop order w
 ith minimal memory overhead. FaSTCC introduces a new 2D tiled contraction-
 index-outer scheme and a corresponding tile-aware design. It outperforms p
 revious state-of-the-art by 2-5x on up to 64 CPU threads.\n\nTag: Research
  & ACM SRC Posters\n\nRecording: Livestreamed, Recorded\n\nRegistration Ca
 tegory: Technical Program Reg Pass\n\nSession Chairs: Eric Schnepf (ISC Gr
 oup); Shashwitha Puttaswamy (George Washington University); Kento Sato (RI
 KEN Center for Computational Science (R-CCS)); Chris Schlipalius (Pawsey S
 upercomputing Research Centre; Commonwealth Scientific and Industrial Rese
 arch Organisation (CSIRO), Australia); and Anja Gerbes (Georg-August-Unive
 rsität Göttingen)\n\n
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