Data Intensive Systems (DIS) Benchmark Performance Summary

Abstract

Peak processor performance increases at a rate of 60% per year, but memory access speeds increase at a rate of only 7% per year. Computing-system designers compensate for the resulting divergence by incorporating caches or latency-hiding measures into their designs. However, elements such as larger caches, prefetching, and multithreading do not address the needs of data-intensive DoD applications, which consequently operate at rates far below the peak processor- capacity. As the mismatch between processor and memory grows the number of applications unable to operate at peak rates increases. The DARPA Data Intensive Systems Program was created to address this problem. A variety of novel architectures or enhancements were developed under this program to increase the effective performance-as opposed to the rated peak performance of systems running data-starved applications. Under this project, a DIS Benchmark Suite was developed to measure the performance of the prototypical systems. Additionally, the DIS Stressmark Suite was developed to assist performance measurement during the development process. Participating teams were expected to utilize these tools and supply their measurements. In this report the benchmarking tools are introduced, the reported results are summarized, and an objective analyses of the results is provided.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2003
Accession Number
ADA418752

Entities

People

  • Joseph Musmanno

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Space

DTIC Thesaurus Topics

  • Computational Science
  • Computer Programming
  • Computer Programs
  • Computers
  • Database Management Systems
  • Databases
  • Detection
  • Detectors
  • Image Processing
  • Information Processing
  • Information Science
  • Information Systems
  • Measurement
  • Operating Systems
  • Target Recognition
  • Three Dimensional
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development
  • Electrical Engineering
  • Parallel and Distributed Computing.