Dynamic load partitioning strategies for managing data of space and time heterogeneity in parallel SAMR applications

Xiaolin Li; Manish Parashar

Dynamic load partitioning strategies for managing data of space and time heterogeneity in parallel SAMR applications

Xiaolin Li, Manish Parashar

Rutgers, The State University

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

5 Scopus citations

Abstract

This paper presents the design and experimental evaluation of two dynamic load partitioning and balancing strategies for parallel Structured Adaptive Mesh Refinement (SAMR) applications: the Level-based Partitioning Algorithm (LPA) and the Hierarchical Partitioning Algorithm (HPA). These techniques specifically address the computational and communication heterogeneity across refinement levels of the adaptive grid hierarchy underlying these methods. An experimental evaluation of the partitioning schemes is also presented.

Original language	English (US)
Pages (from-to)	181-188
Number of pages	8
Journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2790
State	Published - 2004

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Keywords

Dynamic Load Balancing
Parallel and Distributed Computing
Scientific Computing
Structured Adaptive Mesh Refinement

Cite this

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title = "Dynamic load partitioning strategies for managing data of space and time heterogeneity in parallel SAMR applications",

abstract = "This paper presents the design and experimental evaluation of two dynamic load partitioning and balancing strategies for parallel Structured Adaptive Mesh Refinement (SAMR) applications: the Level-based Partitioning Algorithm (LPA) and the Hierarchical Partitioning Algorithm (HPA). These techniques specifically address the computational and communication heterogeneity across refinement levels of the adaptive grid hierarchy underlying these methods. An experimental evaluation of the partitioning schemes is also presented.",

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author = "Xiaolin Li and Manish Parashar",

year = "2004",

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Dynamic load partitioning strategies for managing data of space and time heterogeneity in parallel SAMR applications. / Li, Xiaolin; Parashar, Manish.

In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 2790, 2004, p. 181-188.

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

TY - JOUR

T1 - Dynamic load partitioning strategies for managing data of space and time heterogeneity in parallel SAMR applications

AU - Li, Xiaolin

AU - Parashar, Manish

PY - 2004

Y1 - 2004

N2 - This paper presents the design and experimental evaluation of two dynamic load partitioning and balancing strategies for parallel Structured Adaptive Mesh Refinement (SAMR) applications: the Level-based Partitioning Algorithm (LPA) and the Hierarchical Partitioning Algorithm (HPA). These techniques specifically address the computational and communication heterogeneity across refinement levels of the adaptive grid hierarchy underlying these methods. An experimental evaluation of the partitioning schemes is also presented.

AB - This paper presents the design and experimental evaluation of two dynamic load partitioning and balancing strategies for parallel Structured Adaptive Mesh Refinement (SAMR) applications: the Level-based Partitioning Algorithm (LPA) and the Hierarchical Partitioning Algorithm (HPA). These techniques specifically address the computational and communication heterogeneity across refinement levels of the adaptive grid hierarchy underlying these methods. An experimental evaluation of the partitioning schemes is also presented.

KW - Dynamic Load Balancing

KW - Parallel and Distributed Computing

KW - Scientific Computing

KW - Structured Adaptive Mesh Refinement

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M3 - Article

VL - 2790

SP - 181

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JO - Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

JF - Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

SN - 0302-9743

ER -

Dynamic load partitioning strategies for managing data of space and time heterogeneity in parallel SAMR applications

Abstract

ASJC Scopus subject areas

Keywords

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