Understanding large scale HPC systems through scalable monitoring and analysis.

Conference · Wed Sep 01 04:00:00 EDT 2010

OSTI ID:1028363

Mayo, Jackson R; Chen, Frank Xiaoxiao; Pebay, Philippe Pierre; Wong, Matthew H; Thompson, David; Gentile, Ann C; Roe, Diana C; De Sapio, Vincent; Brandt, James M

As HPC systems grow in size and complexity, diagnosing problems and understanding system behavior, including failure modes, becomes increasingly difficult and time consuming. At Sandia National Laboratories we have developed a tool, OVIS, to facilitate large scale HPC system understanding. OVIS incorporates an intuitive graphical user interface, an extensive and extendable data analysis suite, and a 3-D visualization engine that allows visual inspection of both raw and derived data on a geometrically correct representation of a HPC system. This talk will cover system instrumentation, data collection (including log files and the complications of meaningful parsing), analysis, visualization of both raw and derived information, and how data can be combined to increase system understanding and efficiency.

• Research Organization: Sandia National Laboratories
• Sponsoring Organization: USDOE
• DOE Contract Number: AC04-94AL85000
• OSTI ID: 1028363
• Report Number(s): SAND2010-6158C
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
DATA ANALYSIS
EFFICIENCY
ENGINES
MONITORING
SANDIA NATIONAL LABORATORIES