SY-YEN KUOWinslett MCho YLee JChen Y.2023-06-092023-06-091999https://www.scopus.com/inward/record.uri?eid=2-s2.0-0032659302&doi=10.1145%2f301816.301828&partnerID=40&md5=f4cc4a66f03f9a93a00e7b7b7fe5151bhttps://scholars.lib.ntu.edu.tw/handle/123456789/632102Large simulations which run for hundreds of hours on parallel computers often periodically generate snapshots of states, which are later post-processed to visualize the simulated physical phenomenon. For many applications, fast I/O during post-processing, which is dependent on an efficient organization of data on disk, is as important as minimizing computation-time I/O. In this paper we propose optimizations to support efficient parallel I/O for scientific simulations and subsequent visualizations. We present an ordering mechanism to linearize data on disk, a performance model to help to choose a proper stripe unit size, and a scheduling algorithm to minimize communication contention. Our experiments on an IBM SP show that the combination of these strategies provides a 20-25% performance boost.Algorithms; Computer simulation; File organization; Input output programs; Mathematical models; Natural sciences computing; Optimization; Data organization; Parallel processing systemsjournal article10.1145/301816.3018282-s2.0-0032659302