ScALPEL: A Scalable Adaptive Lightweight Performance Evaluation Library for application performance monitoring

Pyla, Hari and Ramesh, Bharath and Ribbens, Calvin J. and Varadarajan, Srinidhi (2009) ScALPEL: A Scalable Adaptive Lightweight Performance Evaluation Library for application performance monitoring. Technical Report TR-09-03, Computer Science, Virginia Tech.

Abstract

As supercomputers continue to grow in scale and capabilities, it is becoming increasingly difficult to isolate processor and system level causes of performance degradation. Over the last several years, a significant number of performance analysis and monitoring tools have been built/proposed. However, these tools suffer from several important shortcomings, particularly in distributed environments. In this paper we present ScALPEL, a Scalable Adaptive Lightweight Performance Evaluation Library for application performance monitoring at the functional level. Our approach provides several distinct advantages. First, ScALPEL is portable across a wide variety of architectures, and its ability to selectively monitor functions presents low run-time overhead, enabling its use for large-scale production applications. Second, it is run-time configurable, enabling both dynamic selection of functions to profile as well as events of interest on a per function basis. Third, our approach is transparent in that it requires no source code modifications. Finally, ScALPEL is implemented as a pluggable unit by reusing existing performance monitoring frameworks such as Perfmon and PAPI and extending them to support both sequential and MPI applications.