Performance and scaling of locally-structured grid methods for partial differential equations

被引：24

作者：

Colella, Phillip ^{[1
]}

Bell, John ^{[1
]}

Keen, Noel ^{[1
]}

Ligocki, Terry ^{[1
]}

Lijewski, Michael ^{[1
]}

van Straalen, Brian ^{[1
]}

机构：

[1] Lawrence Berkeley Natl Lab, Computat Res Div, 1 Cyclotron Rd, Berkeley, CA 94720 USA

来源：

SCIDAC 2007: SCIENTIFIC DISCOVERY THROUGH ADVANCED COMPUTING | 2007年 / 78卷

关键词：

D O I：

10.1088/1742-6596/78/1/012013

中图分类号：

P1 [天文学];

学科分类号：

0704 ;

摘要：

In this paper, we discuss some of the issues in obtaining high performance for block-structured adaptive mesh refinement software for partial differential equations. We show examples in which AMR scales to thousands of processors. We also discuss a number of metrics for performance and scalability that can provide a basis for understanding the advantages and disadvantages of this approach.

引用

页数：13

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