CTWatch
November 2006 A
High Productivity Computing Systems and the Path Towards Usable Petascale Computing
Jeffrey C. Carver, Mississippi State University
Lorin M. Hochstein, University of Nebraska, Lincoln
Richard P. Kendall, Information Sciences Institute, University of Southern California
Taiga Nakamura, University of Maryland, College Park
Marvin V. Zelkowitz, University of Maryland, College Park; Fraunhofer Center for Experimental Software Engineering
Victor R. Basili, University of Maryland, College Park; Fraunhofer Center for Experimental Software Engineering
Douglass E. Post, DoD High Performance Computing Modernization Office

1
1. Introduction

Computational scientists and engineers face many challenges when writing codes for high-end computing (HEC) systems. With the movement towards peta-scale machines and the increasing focus on improving development productivity, writing a good code is even more challenging. The DARPA High Productivity Computing Systems (HPCS)1 project is developing new machine architectures, programming languages, and software tools to improve the productivity of scientists and engineers 2. Although the existence of these new technologies is important for improving productivity, they will not achieve their stated goals if individual scientists and engineers are not able to effectively use them to solve their problems. A necessary first step in determining the usefulness of new architectures, languages and tools is to gain a better understanding of what the scientists and engineers do, how they do it, and what problems they face in the current HEC development environment. Because the HEC community is very diverse 3, it is necessary to sample different application domains to be able to draw any meaningful conclusions about the commonalties and trends in software development in this community.

This paper discusses some of the similarities and differences found in ten projects taken from different domains as understood by researchers in the HPCS project. We have undertaken a series of case studies to gain deeper insight into the nature of software development for scientific and engineering software. These studies have focused on two different types of projects, (characterized in Table 1):

  • ASC-Alliance projects, DOE-sponsored computational science centers based at University of Illinois Urbana-Champaign, California Institute of Technology, University of Utah, Stanford University, and University of Chicago. In the rest of this paper, the codes are referred to as ASC Codes.
  • Codes from DARPA HPCS mission partners (organizations that have a vested interest in the outcome of and often financial sponsorship of the project), some of which are classified and would therefore be inaccessible to other researchers. Due to the sensitive nature of many of these projects, they must remain anonymous in this paper. In the rest of this paper, these codes are referred to as MP Codes.
ASC Codes MP Codes
# of projects 5 5
Environment Academia (ASC-Alliance projects) Mission Partners (DoD, DOE, NASA)
Classified No Some
Code size 200-600 KLOC 80-760 KLOC
Type Coupled multi-physics applications Single physics to coupled multi-physics and engineering
Table 1. Types of projects examined.

While these case studies are still ongoing, the results to date allow for some cross-project analysis to provide a deeper understanding of the state of the practice 4 5 6 7. In this paper, we discuss some observations gained from this analysis.

Pages: 1 2 3 4 5

Reference this article
Carver, J. C., Hochstein, L. M., Kendall, R. P., Nakamura, T., Zelkowitz, M. V., Basili, V. R., Post, D. E. "Observations about Software Development for High End Computing," CTWatch Quarterly, Volume 2, Number 4A, November 2006 A. http://www.ctwatch.org/quarterly/articles/2006/11/observations-about-software-development-for-high-end-computing/

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