HPCA Workshop on Productivity and Performance in High-End Computing (P-PHEC 2004)

Logistics

• Advance Program
• Workshop Proceedings
• HPCA 2004 Home Page
• Hotel Information
• Registration

Overview

The peak performance of processors has been increasing at an exponential rate, typically doubling every eighteen months. However, this increase in processing capability has not resulted in a corresponding improvement in system productivity for high-end applications and systems. In addition to traditional performance metrics, the productivity of a system is governed by other metrics such as application development time, time to solution, performance portability, robustness, and ease of both correctness validation and performance tuning. With both the range and the complexity of high-end applications continuing to increase, factors other than raw performance are becoming more important to the HEC system user.

Topics

1. Methods, approaches and tools for increasing productivity and/or reducing usage complexity of high-end applications and systems.
2. Productivity metrics: measures of productivity in HEC systems and experiments to validate these measures.
3. Analysis and characterization of HEC workloads and workflows and their distinct requirements.
4. Impact of HEC system properties on time-to-solution or other productivity metrics.
   • The impact of programming models, programming methodologies and programming tools on software productivity for HEC.
   • The impact of HEC system architecture, reliability, robustness and accessibility on productivity.
5. Case studies of productivity measurements and experiments on HEC applications and systems.

Dates and Submissions

Papers should not exceed 15 pages, with double-spaced 11pt size fonts in Adobe PDF format. Please e-mail papers to rajamony@us.ibm.com with the subject: "HPCA Productivity Workshop"

Program Committee

• Victor Basili, University of Maryland College Park
• James Browne, University of Texas Austin
• John Carter, University of Utah
• John Grosh, OSD
• Mary Hall, USC Information Sciences Institute
• Jeremy Kepner, MIT Lincoln Labs
• Karthick Rajamani, IBM Research
• Ram Rajamony, IBM Research (Program Committee Chair)
• Marc Snir, University of Illinois Urbana-Champaign