A Performance Study of a Dual Xeon-Phi Cluster for the Forward Modelling of Gravitational Fields
With at least 60 processing cores, the Xeon-Phi coprocessor is a truly multicore architecture, which consists of an interconnection speed among cores of 240 GB/s, two levels of cache memory, a theoretical performance of 1.01 Tflops, and programming flexibility, all making the Xeon-Phi an excellent c...
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doaj-1b80f59191204d3aaab9d000e9ef46e32021-07-02T05:48:20ZengHindawi LimitedScientific Programming1058-92441875-919X2015-01-01201510.1155/2015/316012316012A Performance Study of a Dual Xeon-Phi Cluster for the Forward Modelling of Gravitational FieldsMaricela Arroyo0Carlos Couder-Castañeda1Alfredo Trujillo-Alcantara2Israel-Enrique Herrera-Diaz3Nain Vera-Chavez4ABACUS-CINVESTAV-IPN, Apartado Postal 14-740, 07000 México City, DF, MexicoABACUS-CINVESTAV-IPN, Apartado Postal 14-740, 07000 México City, DF, MexicoEscuela Superior de Física y Matemáticas, Av. Instituto Politécnico Nacional Edificio 9, Unidad Profesional Adolfo López Mateos, 07738 México City, DF, MexicoDepartment of Industrial Engineering, Campus Celaya-Salvatierra, University of Guanajuato, Mutualismo 303 Colonia Suiza, 38060 Celaya, Gto, MexicoInstituto Mexicano del Petróleo, Eje Central Lázaro Cardenas No. 152, 07730 México City, DF, MexicoWith at least 60 processing cores, the Xeon-Phi coprocessor is a truly multicore architecture, which consists of an interconnection speed among cores of 240 GB/s, two levels of cache memory, a theoretical performance of 1.01 Tflops, and programming flexibility, all making the Xeon-Phi an excellent coprocessor for parallelizing applications that seek to reduce computational times. The objective of this work is to migrate a geophysical application designed to directly calculate the gravimetric tensor components and their derivatives and in this way research the performance of one and two Xeon-Phi coprocessors integrated on the same node and distributed in various nodes. This application allows the analysis of the design factors that drive good performance and compare the results against a conventional multicore CPU. This research shows an efficient strategy based on nested parallelism using OpenMP, a design that in its outer structure acts as a controller of interconnected Xeon-Phi coprocessors while its interior is used for parallelyzing the loops. MPI is subsequently used to reduce the information among the nodes of the cluster.http://dx.doi.org/10.1155/2015/316012 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Maricela Arroyo Carlos Couder-Castañeda Alfredo Trujillo-Alcantara Israel-Enrique Herrera-Diaz Nain Vera-Chavez |
spellingShingle |
Maricela Arroyo Carlos Couder-Castañeda Alfredo Trujillo-Alcantara Israel-Enrique Herrera-Diaz Nain Vera-Chavez A Performance Study of a Dual Xeon-Phi Cluster for the Forward Modelling of Gravitational Fields Scientific Programming |
author_facet |
Maricela Arroyo Carlos Couder-Castañeda Alfredo Trujillo-Alcantara Israel-Enrique Herrera-Diaz Nain Vera-Chavez |
author_sort |
Maricela Arroyo |
title |
A Performance Study of a Dual Xeon-Phi Cluster for the Forward Modelling of Gravitational Fields |
title_short |
A Performance Study of a Dual Xeon-Phi Cluster for the Forward Modelling of Gravitational Fields |
title_full |
A Performance Study of a Dual Xeon-Phi Cluster for the Forward Modelling of Gravitational Fields |
title_fullStr |
A Performance Study of a Dual Xeon-Phi Cluster for the Forward Modelling of Gravitational Fields |
title_full_unstemmed |
A Performance Study of a Dual Xeon-Phi Cluster for the Forward Modelling of Gravitational Fields |
title_sort |
performance study of a dual xeon-phi cluster for the forward modelling of gravitational fields |
publisher |
Hindawi Limited |
series |
Scientific Programming |
issn |
1058-9244 1875-919X |
publishDate |
2015-01-01 |
description |
With at least 60 processing cores, the Xeon-Phi coprocessor is a truly multicore architecture, which consists of an interconnection speed among cores of 240 GB/s, two levels of cache memory, a theoretical performance of 1.01 Tflops, and programming flexibility, all making the Xeon-Phi an excellent coprocessor for parallelizing applications that seek to reduce computational times. The objective of this work is to migrate a geophysical application designed to directly calculate the gravimetric tensor components and their derivatives and in this way research the performance of one and two Xeon-Phi coprocessors integrated on the same node and distributed in various nodes. This application allows the analysis of the design factors that drive good performance and compare the results against a conventional multicore CPU. This research shows an efficient strategy based on nested parallelism using OpenMP, a design that in its outer structure acts as a controller of interconnected Xeon-Phi coprocessors while its interior is used for parallelyzing the loops. MPI is subsequently used to reduce the information among the nodes of the cluster. |
url |
http://dx.doi.org/10.1155/2015/316012 |
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