Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Parallel Solve Phase of a Direct Sparse Solver. / Gumalevskii, Roman V.; Karasenko, Ivan I.; Rakitskiy, Anton A.
24th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2023; Novosibirsk; Russian Federation; 29 June 2023 до 3 July 2023. Institute of Electrical and Electronics Engineers (IEEE), 2023. стр. 1900-1903.Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
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TY - GEN
T1 - Parallel Solve Phase of a Direct Sparse Solver
AU - Gumalevskii, Roman V.
AU - Karasenko, Ivan I.
AU - Rakitskiy, Anton A.
N1 - The research was carried out within the state assignment of Ministry of Science and Higher Education of the Russian Federation (theme No. 123022200042-8)/ Публикация для корректировки.
PY - 2023
Y1 - 2023
N2 - We propose a parallel solve phase algorithm for solving large sparse linear systems arising in wide range of science-intensive and computational applications. In many scenarios, serial solutions of systems with fixed matrix and varied right-hand sides are required. In this case matrix is factorized only once and solve phase is performed many times, so that solve phase becomes the most performance critical part of computations. In this paper, we consider parallel block algorithms of direct and backward substitutions, sequential analogues corresponding to them are also described. We propose a parallelization strategy of the solve phase based on a dynamic two-level scheduling scheme using the nested dissection algorithm. It makes possible independent tasks processing in the subtrees. This reduces synchronization events count and makes the algorithm more efficient. Our parallel solve phase algorithm uses block storage of factorized matrix using a supernodal approach, which allows exploiting the efficiency of the LAPACK and BLAS Level-3 routines.
AB - We propose a parallel solve phase algorithm for solving large sparse linear systems arising in wide range of science-intensive and computational applications. In many scenarios, serial solutions of systems with fixed matrix and varied right-hand sides are required. In this case matrix is factorized only once and solve phase is performed many times, so that solve phase becomes the most performance critical part of computations. In this paper, we consider parallel block algorithms of direct and backward substitutions, sequential analogues corresponding to them are also described. We propose a parallelization strategy of the solve phase based on a dynamic two-level scheduling scheme using the nested dissection algorithm. It makes possible independent tasks processing in the subtrees. This reduces synchronization events count and makes the algorithm more efficient. Our parallel solve phase algorithm uses block storage of factorized matrix using a supernodal approach, which allows exploiting the efficiency of the LAPACK and BLAS Level-3 routines.
UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85172009287&origin=inward&txGid=fb932e4561e6c14b23d1db5ee059dbf4
UR - https://www.mendeley.com/catalogue/0f0b891f-ad8a-3891-8c41-1828e7ea7181/
U2 - 10.1109/edm58354.2023.10225107
DO - 10.1109/edm58354.2023.10225107
M3 - Conference contribution
SN - 9798350336870
SP - 1900
EP - 1903
BT - 24th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2023; Novosibirsk; Russian Federation; 29 June 2023 до 3 July 2023
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -
ID: 59175421