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.
Finally, the Lightweight Distributed Metric Service (LDMS) was developed for performance monitoring at Sandia National Labs REF .
The lightweight distributed metric service: a scalable infrastructure for continuous monitoring of large scale computing systems and applications
SC14: International Conference for High Performance Computing, Networking, Storage and Analysis
SC14: International Conference for High Performance Computing, Networking, Storage and Analysis
Computer Science