PMatlab Takes the HPCchallenge
Abstract
The HPCchallenge benchmark suite has been released by the DARPA HPCS program to help define the performance boundaries of future Petascale computing systems. The suite is composed of several well known computational kernels (STREAM, Top500, FFT, and RandomAccess) that span high and low spatial and temporal locality. These kernels also encompass key aspects of embedded signal processing: vector computations, matrix multiplies, corner turns and random selection operations. MATLAB 2 is the primary high level language used within the signal processing community and is increasingly used for large system simulations and quickly processing data in the field. The pMatlab parallel MATLAB toolbox provides the necessary global array semantics to allow HPCchallenge to be implemented. The results provide a unique opportunity to probe both the relative (pMatlab vs. MATLAB) and absolute (pMatlab vs. C/Fortran+MPI) merits of pMatlab. Specifically, for each kernel in HPCchallenge we examine code size, maximum problem size, and performance. We find pMatlab code to be approximately 10x smaller than the equivalent C/MPI code. The problem sizes possible using pMatlab scale linearly with the number of processors (e.g. we are able to FFT a 2(exp 28) complex vector on 16 CPUS), and are comparable to the corresponding C/Fortran+MPI code. Finally, the scalability of the kernels approaches that of the C/Fortran+MPI code.
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 01, 2005
- Accession Number
- ADA432946
Entities
People
- Albert Reuther
- Andrew Funk
- Charles Rader
- Hahn Kim
- Jeremy Kepner
- Nadya Travinin
- Ryan Haney
Organizations
- Massachusetts Institute of Technology