Hill-climbing SMT processor resource distribution

Abstract

The key to high performance in Simultaneous MultiThreaded (SMT) processors lies in optimizing the distribution of shared resources to active threads. Existing resource distribution techniques optimize performance only indirectly. They infer potential performance bottlenecks by observing indicators, like instruction occupancy or cache miss counts, and take actions to try to alleviate them. While the corrective actions are designed to improve performance, their actual performance impact is not known since end performance is never monitored. Consequently, potential performance gains are lost whenever the corrective actions do not effectively address the actual bottlenecks occurring in the pipeline.

Document Details

Document Type
Pub Defense Publication
Publication Date
Feb 01, 2009
Source ID
10.1145/1482619.1482620

Entities

People

  • Donald Yeung
  • Seungryul Choi

Organizations

  • Air Force Research Laboratory
  • Defense Advanced Research Projects Agency
  • Google
  • National Science Foundation
  • University of Maryland

Tags

Readers

  • Parallel and Distributed Computing.
  • Statistical inference.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks