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

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dc.creatorPyla, Hari K.
dc.creatorRamesh, Bharath
dc.creatorRibbens, Calvin J.
dc.creatorVaradarajan, Srinidhi
dc.date2009-02-28
dc.date.accessioned2026-07-07T12:47:55Z
dc.date.available2026-07-07T12:47:55Z
dc.descriptionAs 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.
dc.description10 pages, 4 figures, 2 tables
dc.identifierhttps://arxiv.org/abs/0903.0035
dc.identifierhttp://arxiv.org/abs/0903.0035
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/221880
dc.subjectDistributed, Parallel, and Cluster Computing
dc.subjectPerformance
dc.titleScALPEL: A Scalable Adaptive Lightweight Performance Evaluation Library for application performance monitoring
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