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HPCMASPA 2016 - Workshop on Monitoring and Analysis for High Performance Computing Systems Plus Applications

Date2016-05-23 - 2016-05-26

Deadline2015-12-18

VenueChicago, USA - United States USA - United States

Keywords

Websitehttps://sites.google.com/site/hpcmaspa2016

Topics/Call fo Papers

Architects, administrators, and users of modern high-performance computing (HPC) systems strive to meet goals of energy, resource, and application efficiency. Optimizing for any or all of these can only be accomplished through analysis of appropriate system and application information. While application performance analysis tools can provide application performance insight, the associated overhead typically decreases application performance while the tools are being employed. Thus they are typically used for application performance tuning but not for production application runs. Likewise traditional system monitoring tools in conjunction with analysis tools can provide insight into run-time system resource utilization. However, due to overhead and impact concerns, such tools are often run with collection periods on order of minutes or only used to solve problems and not during normal HPC system operation. There are currently few, if any, tools that provide continuous, low impact, high fidelity system monitoring, analysis, and feedback that meet the increasingly urgent resource efficiency optimization needs of HPC systems.
Modern processors and operating systems being used in HPC systems expose a wealth of information about how system resources, including energy, are being utilized. Lightweight tools that gather and analyze this information could provide feedback, including run-time, to increase application performance; optimize system resource utilization; and drive more efficient future HPC system design.
The goal of this workshop is to provide an opportunity for researchers to exchange new ideas, research, techniques, and tools in the area of HPC monitoring, analysis, and feedback as it relates to increasing efficiency with respect to energy, resource utilization, and application run-time.

Last modified: 2015-10-17 22:40:05