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Title: A communication-avoiding 3D sparse triangular solver

Conference ·

We present a novel distributed memory algorithm to improve the strong scalability of the solution of a sparse triangular system. This operation appears in the solve phase of direct methods for solving general sparse linear systems, Ax = b. Our 3D sparse triangular solver employs several techniques, including a 3D MPI process grid, elimination tree parallelism, and data replication, all of which reduce the per-process communication when combined. We present analytical models to understand the communication cost of our algorithm and show that our 3D sparse triangular solver can reduce the per-process communication volume asymptotically by a factor of O(n1/4) and O(n1/6) for problems arising from the finite element discretizations of 2D "planar" and 3D "non-planar" PDEs, respectively. We implement our algorithm for use in SuperLU_DIST3D, using a hybrid MPI+OpenMP programming model. Our 3D triangular solve algorithm, when run on 12k cores of Cray XC30, outperforms the current state-of-the-art 2D algorithm by 7.2x for planar and 2.7x for the non-planar sparse matrices, respectively.

Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
DOE Contract Number:
AC05-00OR22725
OSTI ID:
1558528
Resource Relation:
Conference: International Conference on Supercomputing (ICS 2019) - Phoenix, Arizona, United States of America - 6/26/2019 8:00:00 AM-6/28/2019 8:00:00 AM
Country of Publication:
United States
Language:
English

References (16)

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Avoiding communication in sparse matrix computations
  • Demmel, James; Hoemmen, Mark; Mohiyuddin, Marghoob
  • Distributed Processing Symposium (IPDPS), 2008 IEEE International Symposium on Parallel and Distributed Processing https://doi.org/10.1109/IPDPS.2008.4536305
conference April 2008

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