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Statistical assertion: A more powerful method for debugging scientific applications

delete2014-03-01
delete6
PRE
AI
M
Minh Ngoc Dinh *
D
David Abramson
C
Chao Jin
DOI:10.1016/j.jocs.2013.12.002delete
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Abstract

Abstract

En 中文
Traditional debuggers are of limited value for modern scientific codes that manipulate large complex data structures. Current parallel machines make this even more complicated, because the data structure may be distributed across processors, making it difficult to view/interpret and validate its contents. Therefore, many applications' developers resort to placing validation code directly in the source program. This paper discusses a novel debug-time assertion, called a Statistical Assertion, that allows using extracted statistics instead of raw data to reason about large data structures, therefore help locating coding defects. In this paper, we present the design and implementation of an 'extendable' statistical-framework which executes the assertion in parallel by exploiting the underlying parallel system. We illustrate the debugging technique with a molecular dynamics simulation. The performance is evaluated on a 20,000 processor Cray XE6 to show that it is useful for real-time debugging. (C) 2013 Elsevier B.V. All rights reserved.
Keywords:
Debugging
Assertion
Statistics
Parallel architecture

Journal

Nature Computational Science cover
Nature Computational Science
IF:
18.3
Papers:
3.1K
Citations:
4.0K

Organization

M
Monash University
Scholars:
5.4W
Papers: 5.4W
Citations: 79
U
University of Queensland
Scholars:
5.0W
Papers: 5.1W
Citations: 9.2W
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