Presentation
Integrating HPCToolkit with Tools for Automated Analysis
DescriptionHPCToolkit enables users to gather detailed information about application performance. Users can capture fine-grained measurement data, which may include instruction-level samples on CPUs and GPUs. Collected data can be huge, making manual inspection using GUI tools difficult and time-consuming. We explored existing tools Hatchet and Thicket for programmatic analysis of performance data to automate this process. However, they were not designed to handle data as large as HPCToolkit's. HPCToolkit's calling context trees are difficult to interpret and visualize using these tools because of their overwhelming detail. Moreover, importing multiple trees into Thicket can be slow, as unifying trees is costly when trees are large. To reduce the size of large trees, we implemented heuristics that would automatically detect and remove specific code regions. After creating smaller trees that we believe contain all the meaningful information about the program's behavior, we used Thicket to analyze multiple performance profiles measured by HPCToolkit.
Event Type
ACM Student Research Competition: Graduate Poster
ACM Student Research Competition: Undergraduate Poster
Doctoral Showcase
Posters
TimeTuesday, 19 November 202412pm - 5pm EST
LocationB302-B305
TP
XO/EX