Abstract
In this paper we present an approach to online automatic monitoring of memory hierarchies in threaded applications. Our environment consists of a monitoring system and an automatic performance analysis tool. The CMM monitoring system uses static instrumentation of the source code and information from the hardware counters to generate performance data for selected code regions and data structures. The monitor supports threaded applications by providing per-thread performance data or by aggregating it. It also provides a monitoring request API for the performance tools. Our tool AMEBA performs an online automatic search for cache and thread-related ASL properties in the code. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Kereku, E., & Gerndt, M. (2007). Automatic monitoring of memory hierarchies in threaded applications with AMEBA. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4699 LNCS, pp. 420–429). Springer Verlag. https://doi.org/10.1007/978-3-540-75755-9_51
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