WIT Press


Performance Assessment Of Parallel Techniques

Price

Free (open access)

Paper DOI

10.2495/DATA070091

Volume

38

Pages

10

Published

2007

Size

372 kb

Author(s)

T. Grytsenko & A. Peratta

Abstract

The goal of this work is to evaluate and compare the computational performance of the most common parallel libraries such as Message Passing Interface (MPI), High Performance Fortran (HPF), OpenMP and DVM for further implementations. Evaluation is based on NAS Parallel benchmark suite (NPB) which includes simulated applications BT, SP, LU and kernel benchmarks FT, CG and MG. A brief introduction of the four parallel techniques under study: MPI, HPF, OpenMP and DVM, as well as their models is provided together with benchmarks used and the test results. Finally, corresponding recommendations are given for the different approaches depending on the number of processors. Keywords: MPI, HPL, DVM, OpenMP, parallel programming, performance, parallel calculations. 1 Introduction This section provides a brief introduction of the four parallel techniques under study: MPI, HPF, OpenMP and DVM, as well as their models. 1.1 The Message-Passing Information programming model (MPI) Programming models are generally categorised according to the way in which how memory is used. In the shared memory model each process accesses a shared address space, while in the message passing model an application runs as a collection of autonomous processes, each with its own local memory. In the message passing model processes communicate with other processes by sending and receiving messages (see Figure 1). When data is passed in a message, the sending and receiving processes must work to transfer the data from the local memory of one to the local memory of the other.

Keywords

MPI, HPL, DVM, OpenMP, parallel programming, performance, parallel calculations.