Optimizing noncontiguous accesses in MPI-IO.

Journal Article · Tue Jan 01 04:00:00 EST 2002 · Parallel Comput.

DOI:https://doi.org/10.1016/S0167-8191(01)00129-6· OSTI ID:943133

Thakur, R; Gropp, W; Lusk, E

The I/O access patterns of many parallel applications consist of accesses to a large number of small, noncontiguous pieces of data. If an application's I/O needs are met by making many small, distinct I/O requests, however, the I/O performance degrades drastically. To avoid this problem, MPI-IO allows users to access noncontiguous data with a single I/O function call, unlike in Unix I/O. In this paper, we explain how critical this feature of MPI-IO is for high performance and how it enables implementations to perform optimizations. We first provide a classification of the different ways of expressing an application's I/O needs in MPI-IO -- we classify them into four levels, called levels 0--3. We demonstrate that, for applications with noncontiguous access patterns, the I/O performance improves dramatically if users write their applications to make level-3 requests (noncontiguous, collective) rather than level-0 requests (Unix style). We then describe how our MPI-IO implementation, ROMIO, delivers high performance for noncontiguous requests. We explain in detail the two key optimizations ROMIO performs: data sieving for noncontiguous requests from one process and collective I/O for noncontiguous requests from multiple processes. We describe how we have implemented these optimizations portably on multiple machines and file systems, controlled their memory requirements, and also achieved high performance. We demonstrate the performance and portability with performance results for three applications -- an astrophysics-application template (DIST3D), the NAS BTIO benchmark, and an unstructured code (UNSTRUC) -- on five different parallel machines: HP Exemplar, IBM SP, Intel Paragon, NEC SX-4, and SGI Origin2000.

• Research Organization: Argonne National Laboratory (ANL)
• Sponsoring Organization: SC; DOD; NSF
• DOE Contract Number: AC02-06CH11357
• OSTI ID: 943133
• Report Number(s): ANL/MCS/JA-37760
• Journal Information: Parallel Comput., Journal Name: Parallel Comput. Journal Issue: 1 ; Jan. 2002 Vol. 28; ISSN PACOEJ; ISSN 0167-8191
• Country of Publication: United States
• Language: ENGLISH

Related Subjects

99 GENERAL AND MISCELLANEOUS
COMPUTER CODES
DATA
MEMORY MANAGEMENT
OPTIMIZATION
PARALLEL PROCESSING
PERFORMANCE