@inproceedings{7bdcf4c9768f49afabc86cabc41559b8,
title = "On using incremental profiling for the performance analysis of shared memory parallel applications",
abstract = "Profiling is often the method of choice for performance analysis of parallel applications due to its low overhead and easily comprehensible results. However, a disadvantage of profiling is the loss of temporal information that makes it impossible to causally relate performance phenomena to events that happened prior or later during execution. We investigate techniques to add temporal dimension to profiling data by incrementally capturing profiles during the runtime of the application and discuss the insights that can be gained from this type of performance data. The context in which we explore these ideas is an existing profiling tool for OpenMP applications.",
author = "Karl Fuerlinger and Michael Gerndt and Jack Dongarra",
year = "2007",
doi = "10.1007/978-3-540-74466-5_8",
language = "English",
isbn = "9783540744658",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "62--71",
booktitle = "Euro-Par 2007 Parallel Processing - 13th International Euro-Par Conference, Proceedings",
note = "13th International Euro-Par Conference on Parallel Processing, Euro-Par 2007 ; Conference date: 28-08-2007 Through 31-08-2007",
}