No abstract

Cluster computing has been attracting more and more attention from both the industry and the academia for its enormous computing power, cost effectiveness, and scalability. Availability is a key system attribute that needs to be considered both at system design stage and must reflect the actuality. System monitoring and logging enables identifying unplanned events to reflect the actual system's availability. This paper proposes a single framework that coordinates event monitoring, filtering, data analysis and dynamic availability modeling. The availability model is abstracted and categorized based on functionality. We describe the proposed architecture, and a sample analysis of real time event logs from a 512 node cluster from Lawrence Livermore National Laboratory.

No abstract

MOLAR is a multi-institutional research effort that concentrates on adaptive, reliable, and efficient operating and runtime system (OS/R) solutions for ultra-scale high-end scientific computing on the next generation of supercomputers. This research addresses the challenges outlined in FAST-OS (forum to address scalable technology for runtime and operating systems) and HECRTF (high-end computing revitalization task force) activities by exploring the use of advanced monitoring and adaptation to improve application performance and predictability of system interruptions, and by advancing computer reliability, availability and serviceability (RAS) management systems to work cooperatively with the OS/R to identify and preemptively resolve system issues. This paper describes recent research of the MOLAR team in advancing RAS for high-end computing OS/Rs.