STTR Phase I: Fault-Tolerant MPI: An Enabling Strategy, Product Concept, and Enhancement of Production Cluster Computing

Award Information
Agency: National Science Foundation
Branch: N/A
Contract: 0340071
Agency Tracking Number: 0340071
Amount: $99,958.00
Phase: Phase I
Program: STTR
Awards Year: 2004
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
110 12th Street North, Birmingham, AL, 35203
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Pirabhu Raman
 (205) 314-3471
Business Contact
 Jennifer Herrett-Skjellum
Phone: (662) 320-4300
Research Institution
 University of Florida
 Alan George
 218 Grinter Hall
Gainsville, FL, 32611
 (352) 392-1582
 Nonprofit college or university
This Small Business Technology Transfer Research (STTR) Phase I proposal proposes to develop a scalable, fault-tolerant and reliable message-passing interface. MPI-2 is a key technology for the next several years in enabling scalable parallel computing on massively parallel machines and Beowulf clusters. Fault-tolerance is absent in both the MPI-1 and MPI-2 standards, and no satisfactory products or research results offer an effective path to providing production scalable computing applications with effective fault-tolerance. This proposal addresses fault-tolerance in both the MPI-1 and MPI-2 standards, with attention to key application classes, fault-free overhead, and checkpoint-restart strategies. It connects the resource management infrastructure in use by many types of MPI users in science and industry with the fault-tolerant mechanisms, to be useful in practical scientific computing. If successful this product will provide key new capabilities to parallel programs, programmers, and cluster systems, including the enhancement of existing commercial applications based on MPI, such as CFD applications. The proposed effort is the first towards realizing a fault-tolerant MPI-2, a technology that would be exploited by scientists and engineers across the spectrum, since parallel computing based on MPI is a widespread enabler of scientific discovery. The project expects to increase the adoption of MPI-2, as well as higher productivity parallel computing for clusters and potentially for the grid. The computer science and engineering experience gained through this work will enable better interoperation of MPI implementations and resource allocators, which in turn will further enable efficient production parallel computing. The optimizations targeted at the popular recovery mechanisms, for key classes of applications, can be applied to any middleware and hence would result in improving the performance of applications in general.

* Information listed above is at the time of submission. *

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