ACM Home Page
Please provide us with feedback. Feedback
OMPI: optimizing MPI programs using partial evaluation
Full text PdfPdf (139 KB)
Source Conference on High Performance Networking and Computing archive
Proceedings of the 1996 ACM/IEEE conference on Supercomputing (CDROM) table of contents
Pittsburgh, Pennsylvania, United States
Article No. 37  
Year of Publication: 1996
ISBN:0-89791-854-1
Authors
Hirotaka Ogawa  Department of Information Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113, Japan
Satoshi Matsuoka  Department of Information Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113, Japan
Sponsor
SIGARCH: ACM Special Interest Group on Computer Architecture
Publisher
IEEE Computer Society  Washington, DC, USA
Bibliometrics
Downloads (6 Weeks): 6,   Downloads (12 Months): 20,   Citation Count: 5
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/369028.369106
What is a DOI?

ABSTRACT

MPI is gaining acceptance as a standard for message-passing in high-performance computing, due to its powerful and flexible support of various communication styles. However, the complexity of its API poses significant software overhead, and as a result, applicability of MPI has been restricted to rather regular, coarse-grained computations. Our OMPI (Optimizing MPI) system removes much of the excess overhead by employing partial evaluation techniques, which exploit static information of MPI calls. Because partial evaluation alone is insufficient, we also utilize template functions for further optimization. To validate the effectiveness for our OMPI system, we performed baseline as well as more extensive benchmarks on a set of application cores with different communication characteristics, on the 64-node Fujitsu AP1000 MPP. Benchmarks show that OMPI improves execution efficiency by as much as factor of two for communication-intensive application core with minimal code increase. It also performs significantly better than previous dynamic optimization technique.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
H. Franke, P. Hochschild, P. Pattnaik, J. Prost, and M. Snir. MPI on IBM SP1/SP2: Current status and future directions. In Proceedings of 1994 Scalable Parallel Libraries. October 1994.
 
2
K. Konishi, Y. Takano, and A. Konagaya. MPI/DE: and MPI library for Cenju-3. In MPI Developers Conference, University of Notre Dame, June 1995.
 
3
D. Sitsky and K. Hayashi. Implementing MPI for the Fujitsu AP1000/AP1000+ using Polling, Interrupts and Remote Copying. In Proceedings of Joint Symposium on Parallel Processing '96, University of Waseda, Japan. June 1996. (to be submitted)
4
 
5
R. Wilson, R. French, C. Wilson, S. Amrasinghe, J. Anderson, S. Tjiang, S-W. Liao, C-W. Tseng, M. Hall, M. Lam, and J. Hennessy. The SUIF Compiler System. Computer Systems Laboratory, Stanford University, 1994.
 
6
Message-Passing Interface Forum. MPI: A message passing interface standard, version 1.1. June 1995.
 
7
8
9
 
10


Collaborative Colleagues:
Hirotaka Ogawa: colleagues
Satoshi Matsuoka: colleagues