By Topic

High-Performance and Scalable MPI over InfiniBand with Reduced Memory Usage: An In-Depth performance Analysis

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Sur, S. ; Dept. of Comput. Sci. & Eng., Ohio State Univ., Columbus, OH ; Koop, M.J. ; Panda, D.K.

InfiniBand is an emerging HPC interconnect being deployed in very large scale clusters, with even larger InfiniBand-based clusters expected to be deployed in the near future. The message passing interface (MPI) is the programming model of choice for scientific applications running on these large scale clusters. Thus, it is very critical for the MPI implementation used to be based on a scalable and high-performance design. We analyze the performance and scalability aspects of MVAPICH, a popular open-source MPI implementation on InfiniBand, from an application standpoint. We analyze the performance and memory requirements of the MPI library while executing several well-known applications and benchmarks, such as NAS, SuperLU, NAMD, and HPL on a 64-node InfiniBand cluster. Our analysis reveals that latest design of MVAPICH requires an order of magnitude less internal MPI memory (average per process) and yet delivers the best possible performance. Further, we observe that for these benchmarks and applications evaluated, the internal memory requirement of MVAPICH remains nearly constant at around 5-10 MB as the number of processes increase, indicating that the MVAPICH design is highly scalable

Published in:

SC 2006 Conference, Proceedings of the ACM/IEEE

Date of Conference:

11-17 Nov. 2006