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DOE OSTI · 1764239

Asynchronous Iterative Solvers for Extreme-Scale Computing

Dongarra, Jack·Tomov, Stanimire·Anzt, Hartwig
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Abstract

The Asynchronous Iterative Solvers for Extreme-Scale Computing (AsyncIS) project aims to explore more efficient numerical algorithms by decreasing their overhead. AsyncIS does this by replacing the outer Krylov subspace solver with an asynchronous optimized Schwarz method, thereby removing the global synchronization and bulk synchronous operations typically used in numerical codes. AsyncIS—a U.S. Department of Energy (DOE)-funded collaboration between Georgia Tech, the University of Tennessee, Knoxville, Temple University, and Sandia National Laboratories—also focuses on the development and optimization of asynchronous preconditioners (i.e., preconditioners that are generated and/or applied in an asynchronous fashion). The novel preconditioning algorithms that provide fine-grained parallelism enable preconditioned Krylov solvers to run efficiently on large-scale distributed systems and manycore accelerators like GPUs.

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97 MATHEMATICS AND COMPUTINGGPUheterogeneous computinghigh performance computingkrylov solversnumerical linear algebraoptimized Schwarz method

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Dongarra, Jack, Tomov, Stanimire, Anzt, Hartwig. 2021-02-04. Asynchronous Iterative Solvers for Extreme-Scale Computing. https://doi.org/10.2172/1764239

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