Improved parallelization techniques for the density matrix renormalization group

Julián Rincón; D. J. García; K. Hallberg

doi:10.1016/j.cpc.2010.03.018

Improved parallelization techniques for the density matrix renormalization group

Julián Rincón
, D. J. García
, K. Hallberg

Producción científica: Contribución a revista › Artículo de Investigación › revisión exhaustiva

8 Citas (Scopus)

Resumen

A distributed-memory parallelization strategy for the density matrix renormalization group is proposed for cases where correlation functions are required. This new strategy has substantial improvements with respect to previous works. A scalability analysis shows an overall serial fraction of 9.4% and an efficiency of around 60% considering up to eight nodes. Sources of possible parallel slowdown are pointed out and solutions to circumvent these issues are brought forward in order to achieve a better performance.

Idioma original	Inglés estadounidense
Páginas (desde-hasta)	1346-1351
Número de páginas	6
Publicación	Computer Physics Communications
Volumen	181
N.º	8
DOI	https://doi.org/10.1016/j.cpc.2010.03.018
Estado	Publicada - ago. 2010
Publicado de forma externa	Sí

Áreas temáticas de ASJC Scopus

Hardware y arquitectura
Física y Astronomía General

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10.1016/j.cpc.2010.03.018

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title = "Improved parallelization techniques for the density matrix renormalization group",

abstract = "A distributed-memory parallelization strategy for the density matrix renormalization group is proposed for cases where correlation functions are required. This new strategy has substantial improvements with respect to previous works. A scalability analysis shows an overall serial fraction of 9.4\% and an efficiency of around 60\% considering up to eight nodes. Sources of possible parallel slowdown are pointed out and solutions to circumvent these issues are brought forward in order to achieve a better performance.",

author = "Juli{\'a}n Rinc{\'o}n and Garc{\'i}a, \{D. J.\} and K. Hallberg",

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AU - García, D. J.

AU - Hallberg, K.

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AB - A distributed-memory parallelization strategy for the density matrix renormalization group is proposed for cases where correlation functions are required. This new strategy has substantial improvements with respect to previous works. A scalability analysis shows an overall serial fraction of 9.4% and an efficiency of around 60% considering up to eight nodes. Sources of possible parallel slowdown are pointed out and solutions to circumvent these issues are brought forward in order to achieve a better performance.

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UR - https://www.scopus.com/pages/publications/77953128677#tab=citedBy

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DO - 10.1016/j.cpc.2010.03.018

M3 - Research Article

AN - SCOPUS:77953128677

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JO - Computer Physics Communications

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Improved parallelization techniques for the density matrix renormalization group

Resumen

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