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Title: Static analysis techniques for semiautomatic synthesis of message passing software skeletons

Journal Article · · ACM Transactions on Modeling and Computer Simulation
DOI:https://doi.org/10.1145/2778888· OSTI ID:1183091
 [1];  [1];  [2];  [3];  [4]
  1. Galois, Inc., Portland, OR (United States). Research and Engineering
  2. Univ. of Central Florida, Orlando, FL (United States)
  3. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
  4. Sandia National Lab. (SNL-CA), Livermore, CA (United States); Univ. of Central Florida, Orlando, FL (United States)

The design of high-performance computing architectures demands performance analysis of large-scale parallel applications to derive various parameters concerning hardware design and software development. The process of performance analysis and benchmarking an application can be done in several ways with varying degrees of fidelity. One of the most cost-effective ways is to do a coarse-grained study of large-scale parallel applications through the use of program skeletons. The concept of a “program skeleton” that we discuss in this article is an abstracted program that is derived from a larger program where source code that is determined to be irrelevant is removed for the purposes of the skeleton. In this work, we develop a semiautomatic approach for extracting program skeletons based on compiler program analysis. Finally, we demonstrate correctness of our skeleton extraction process by comparing details from communication traces, as well as show the performance speedup of using skeletons by running simulations in the SST/macro simulator.

Research Organization:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
AC04-94AL85000
OSTI ID:
1183091
Report Number(s):
SAND-2014-16866J; 536718
Journal Information:
ACM Transactions on Modeling and Computer Simulation, Vol. 26, Issue 1; ISSN 1049-3301
Publisher:
ACMCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 2 works
Citation information provided by
Web of Science