Dynamic-CoMPI: Dynamic optimization techniques for MPI parallel applications

Rosa Filgueira, Jesús Carretero, David E. Singh, Alejandro Calderón, Alberto Núñez

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

This work presents an optimization of MPI communications, called Dynamic-CoMPI, which uses two techniques in order to reduce the impact of communications and non-contiguous I/O requests in parallel applications. These techniques are independent of the application and complementaries to each other. The first technique is an optimization of the Two-Phase collective I/O technique from ROMIO, called Locality aware strategy for Two-Phase I/O (LA-Two-Phase I/O). In order to increase the locality of the file accesses, LA-Two-Phase I/O employs the Linear Assignment Problem (LAP) for finding an optimal I/O data communication schedule. The main purpose of this technique is the reduction of the number of communications involved in the I/O collective operation. The second technique, called Adaptive-CoMPI, is based on run-time compression of MPI messages exchanged by applications. Both techniques can be applied on every application, because both of them are transparent for the users. Dynamic-CoMPI has been validated by using several MPI benchmarks and real HPC applications. The results show that, for many of the considered scenarios, important reductions in the execution time are achieved by reducing the size and the number of the messages. Additional benefits of our approach are the reduction of the total communication time and the network contention, thus enhancing, not only performance, but also scalability.

Original languageEnglish
Pages (from-to)361-391
Number of pages31
JournalJournal of Supercomputing
Volume59
Issue number1
DOIs
Publication statusPublished - Jan 2012

Keywords

  • Adaptive systems
  • Clusters architectures
  • Collective I/O
  • Compression algorithms
  • Heuristics
  • MPI library
  • Parallel techniques

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Information Systems
  • Hardware and Architecture

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