Massively parallel, three-dimensional transport solutions for the k-eigenvalue problem

Gregory G. Davidson; Thomas M. Evans; Joshua J. Jarrell; Steven P. Hamilton; Tara M. Pandya; Rachel N. Slaybaugh

doi:10.13182/NSE12-101

Massively parallel, three-dimensional transport solutions for the k-eigenvalue problem

Gregory G. Davidson, Thomas M. Evans, Joshua J. Jarrell, Steven P. Hamilton, Tara M. Pandya, Rachel N. Slaybaugh

Research output: Contribution to journal › Article › peer-review

25 Scopus citations

Abstract

We have implemented a new multilevel parallel decomposition in the Denovo discrete ordinates radiation transport code. In concert with Krylov subspace iterative solvers, the multilevel decomposition allows concurrency over energy in addition to space-angle, enabling scalability beyond the limits imposed by the traditional Koch-Baker-Alcouffe (KBA) space-angle partitioning. Furthermore, a new Arnoldi-based k-eigenvalue solver has been implemented. The added phase-space concurrency combined with the high-performance Krylov and Arnoldi solvers has enabled weak scaling to 0(10⁵) cores on the Titan XK7 supercomputer. The multilevel decomposition provides a mechanism for scaling to exascale computing and beyond.

Original language	English
Pages (from-to)	111-125
Number of pages	15
Journal	Nuclear Science and Engineering
Volume	177
Issue number	2
DOIs	https://doi.org/10.13182/NSE12-101
State	Published - Jun 2014

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abstract = "We have implemented a new multilevel parallel decomposition in the Denovo discrete ordinates radiation transport code. In concert with Krylov subspace iterative solvers, the multilevel decomposition allows concurrency over energy in addition to space-angle, enabling scalability beyond the limits imposed by the traditional Koch-Baker-Alcouffe (KBA) space-angle partitioning. Furthermore, a new Arnoldi-based k-eigenvalue solver has been implemented. The added phase-space concurrency combined with the high-performance Krylov and Arnoldi solvers has enabled weak scaling to 0(105) cores on the Titan XK7 supercomputer. The multilevel decomposition provides a mechanism for scaling to exascale computing and beyond.",

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AU - Pandya, Tara M.

AU - Slaybaugh, Rachel N.

PY - 2014/6

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AB - We have implemented a new multilevel parallel decomposition in the Denovo discrete ordinates radiation transport code. In concert with Krylov subspace iterative solvers, the multilevel decomposition allows concurrency over energy in addition to space-angle, enabling scalability beyond the limits imposed by the traditional Koch-Baker-Alcouffe (KBA) space-angle partitioning. Furthermore, a new Arnoldi-based k-eigenvalue solver has been implemented. The added phase-space concurrency combined with the high-performance Krylov and Arnoldi solvers has enabled weak scaling to 0(105) cores on the Titan XK7 supercomputer. The multilevel decomposition provides a mechanism for scaling to exascale computing and beyond.

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Massively parallel, three-dimensional transport solutions for the k-eigenvalue problem

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