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Two-Phase IO Enabling Large-Scale Performance Introspection
SessionPoster Reception
DescriptionNumerous sophisticated profiling and visualization tools have been developed to enable programmers to expose semantic information from their application components. However, effective and interactive exploration of the profiles of large-scale parallel programs remains a challenge due to the high I/O overheads of profiles and the difficulties in scaling downstream visualization tools. In this poster, we present a full-stack approach to a performance introspection framework that tackles key challenges in profiling and visualizing performance data at scale. Our novelty lies in a scalable and compact data model and a two-phase I/O system, which instill scalability into the profiler making it low overhead-- even at high process counts (< 5%). We then build a web-based, visual-analytic dashboard with linked views. Our profiling and visualization tools are both lightweight and easy-to-use, which strikes a balance between providing sophisticated features and operating quickly and efficiently at high process counts.
Event Type
ACM Student Research Competition: Graduate Poster
ACM Student Research Competition: Undergraduate Poster
Doctoral Showcase
Posters
Research Posters
Scientific Visualization & Data Analytics Showcase
TimeTuesday, 14 November 20235:15pm - 7pm MST
LocationDEF Concourse
Performance Measurement, Modeling, and Tools
TP