Abstract
Understanding how resources of High Performance Compute platforms are utilized by applications both individually and as a composite is key to application and platform performance. Typical system monitoring tools do not provide sufficient fidelity while application profiling tools do not capture the complex interplay between applications competing for shared resources. To gain new insights, monitoring tools must run continuously, system wide, at frequencies appropriate to the metrics of interest while having minimal impact on application performance. We introduce the Lightweight Distributed Metric Service for scalable, lightweight monitoring of large scale computing systems and applications. We describe issues and constraints guiding deployment in Sandia National Laboratories' capacity computing environment and on the National Center for Supercomputing Applications' Blue Waters platform including motivations, metrics of choice, and requirements relating to the scale and specialized nature of Blue Waters. We address monitoring overhead and impact on application performance and provide illustrative profiling results.
Original language | English (US) |
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Article number | 7013000 |
Pages (from-to) | 154-165 |
Number of pages | 12 |
Journal | International Conference for High Performance Computing, Networking, Storage and Analysis, SC |
Volume | 2015-January |
Issue number | January |
DOIs | |
State | Published - Jan 16 2014 |
Event | International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2014 - New Orleans, United States Duration: Nov 16 2014 → Nov 21 2014 |
Keywords
- resource management
- resource monitoring
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Hardware and Architecture
- Software