Improving MPI Independent Write Performance Using A Two-Stage Write-Behind Buffering Method

Many large-scale production applications often have very long executions times and require periodic data checkpoints in order to save the state of the computation for program restart and/or tracing application progress. These write-only operations often dominate the overall application runtime, which makes them a good optimization target. Existing approaches for write-behind data buffering at the MPI I/O level have been proposed, but challenges still exist for addressing system-level I/O issues. We propose a twostage write-behind buffering scheme for handing checkpoint operations. The first-stage of buffering accumulates write data for better network utilization and the second-stage of buffering enables the alignment for the write requests to the file stripe boundaries. Aligned I/O requests avoid file lock contention that can seriously degrade I/O performance. We present our performance evaluation using BTIO benchmarks on both GPFS and Lustre file systems. With the twostage buffering, the performance of BTIO through MPI independent I/O is significantly improved and even surpasses that of collective I/O. 1

Improving Parallel I/O Performance Using Interval I/O

Today\u27s most advanced scientific applications run on large clusters consisting of hundreds of thousands of processing cores, access state of the art parallel file systems that allow files to be distributed across hundreds of storage targets, and utilize advanced interconnections systems that allow for theoretical I/O bandwidth of hundreds of gigabytes per second. Despite these advanced technologies, these applications often fail to obtain a reasonable proportion of available I/O bandwidth. The reasons for the poor performance of application I/O include the noncontiguous I/O access patterns used for scientific computing, contention due to false sharing, and the somewhat finicky nature of parallel file system performance. We argue that a more fundamental cause of this problem is the legacy view of a file as a linear sequence of bytes. To address these issues, we introduce a novel approach for parallel I/O called Interval I/O. Interval I/O is an innovative approach that uses application access patterns to partition a file into a series of intervals, which are used as the fundamental unit for subsequent I/O operations. Use of this approach provides superior performance for the noncontiguous access patterns which are frequently used by scientific applications. In addition, the approach reduces false contention and the unnecessary serialization it causes. Interval I/O also significantly increases the performance of atomic mode operations. Finally, the Interval I/O approach includes a technique for supporting parallel I/O for cooperating applications. We provide a prototype implementation of our Interval I/O system and use it to demonstrate performance improvements of as much as 1000% compared to ROMIO when using Interval I/O with several common benchmarks