Tuning the performance of I/O-intensive parallel applications

Getting good I/O performance from parallel programs is a critical problem for many application domains. In this paper, we report our experience tuning the I/O performance of four application programs from the areas of satellite-data processing and linear algebra. After tuning, three of the four applications achieve application-level I/O rates of over 100 MB/s on 16 processors. The total volume of I/O required by the programs ranged from about 75 MB to over 200 GB. We report the lessons learned in achieving high I/O performance from these applications, including the need for code restructuring, local disks on every node and knowledge of future I/O requests. We also report our experience on achieving high performance on peer-to-peer con gurations. Finally, we comment on the necessity of complex I/O interfaces like collective I/O and strided requests to achieve high performance.