SCALA: A Framework for Performance Evaluation of Scalable Computing
Xian-He Sun(Louisiana State University
), Mario Pantano(Louisiana State University
), Thomas Fahringer(University of Illinios
), Zhaohua Zhan(University of Illinios
)
To appear at (HIPS'99), San Juan, Puerto Rico, USA, April 12, 1999
Abstract
Lack of effective performance-evaluation environments is a major
barrier to the broader use of high performance computing.
Conventional performance environments are based on profiling and
event instrumentation. It becomes problematic as parallel systems
scale to hundreds of nodes and beyond. A framework of developing an
integrated performance modeling and prediction system,
SCALability Analyzer (SCALA), is presented in this study.
In contrast to existing performance tools, the program performance
model generated by SCALA is based on scalability analysis.
SCALA assumes the availability of modern compiler technology,
adopts statistical methodologies, and has the support of browser interface.
These technologies, together with a new approach of scalability analysis,
enable SCALA to provide the user with a higher and more intuitive level of
performance analysis for scalable computing. SCALA is designed
to explore the validity of these new techniques, and use them collectively
to bring performance analysis environment to the most advanced level.
A prototype SCALA system has been implemented. Initial experimental
results show that SCALA is unique in its ability of revealing the
scaling properties of a computing system. It is a complement of existing
performance environments and has a real potential.
