Keywords
Program skeleton, static analysis, dependency analysis, simulation, source to source code generation
Abstract
The design of high-performance computing architectures requires performance analysis of largescale 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 paper 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 semi-automatic approach for extracting program skeletons based on compiler program analysis. 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. Extracting such a program skeleton from a large-scale parallel program requires a substantial amount of manual effort and often introduces human errors. We outline a semi-automatic approach for extracting program skeletons from large-scale parallel applications that reduces cost and eliminates errors inherent in manual approaches. Our skeleton generation approach is based on the use of the extensible and open-source ROSE compiler infrastructure that allows us to perform flow and dependency analysis on larger programs in order to determine what code can be removed from the program to generate a skeleton.
Notes
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Graduation Date
2013
Semester
Spring
Advisor
Dechev, Damian
Degree
Master of Science (M.S.)
College
College of Engineering and Computer Science
Department
Electrical Engineering and Computer Science
Degree Program
Computer Science
Format
application/pdf
Identifier
CFE0004743
URL
http://purl.fcla.edu/fcla/etd/CFE0004743
Language
English
Release Date
May 2013
Length of Campus-only Access
None
Access Status
Masters Thesis (Open Access)
Subjects
Dissertations, Academic -- Engineering and Computer Science, Engineering and Computer Science -- Dissertations, Academic
STARS Citation
Dakshinamurthy, Amruth Rudraiah, "A Compiler-based Framework For Automatic Extraction Of Program Skeletons For Exascale Hardware/software Co-design" (2013). Electronic Theses and Dissertations. 2576.
https://stars.library.ucf.edu/etd/2576