Optimizing center performance through coordinated data staging, scheduling and recovery

Procurement and the optimized utilization of Petascale supercomputers and centers is a renewed national priority. Sustained performance and availability of such large centers is a key technical challenge significantly impacting their usability. Storage systems are known to be the primary fault source leading to data unavailability and job resubmissions. This results in reduced center performance, partially due to the lack of coordination between I/O activities and job scheduling. In this work, we propose the coordination of job scheduling with data staging/offloading and on-demand staged data reconstruction to address the availability of job input data and to improve center-wide performance. Fundamental to both mechanisms is the efficient management of transient data: in the way it is scheduled and recovered. Collectively, from a center's standpoint, these techniques optimize resource usage and increase its data/service availability. From a user's standpoint, they reduce the job turnaround time and optimize the allocated time usage.