Abstract
Petascale systems are in existence today and will become common in the next few years. Such systems are inevitably very complex, highly distributed and heterogeneous. Monitoring a petascale system in real-time and understanding its status at any given moment without impacting its performance is a highly intricate task. Common approaches and off-the-shelf tools are either unusable, do not scale, or severely impact the performance of the monitored servers. This paper describes unobtrusive monitoring software developed at Stanford Linear Accelerator Center (SLAC) for a highly distributed petascale production data set. The paper describes the employed solutions, the lessons learned, the problems still to be addressed, and explains how the system can be reused elsewhere
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
