1 / 12

Path Profile Estimation and Superblock Formation

Path Profile Estimation and Superblock Formation. Jeff Pang Jimeng Sun. Motivation. Continuous Optimization Dynamic Optimization Realistic Profiles. Compile. Optimize. Run. Profile. Challenges. Automate optimization Low overhead profiling Accurate profiling. Compile. Optimize. Run.

jariah
Télécharger la présentation

Path Profile Estimation and Superblock Formation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Path Profile Estimation and Superblock Formation Jeff Pang Jimeng Sun 15-745 Spring 2005

  2. Motivation • Continuous Optimization • Dynamic Optimization • Realistic Profiles Compile Optimize Run Profile 15-745 Spring 2005

  3. Challenges • Automate optimization • Low overhead profiling • Accurate profiling Compile Optimize Run Sample Estimate Profile Path Profile 15-745 Spring 2005

  4. Project Goals Superblock Formation Run with Simulated PMU • Simulate performance monitoring unit • Like in Pentium 4, Itanium, PPC 970, etc. • Allows sampling of last couple branches • Estimate full path profile using samples • Leverage data mining techniques similar to PageRank • Validate by doing Superblock formation • Powerful optimization to improve scheduling (especially on VLIW processors) Path Profile Sample Data Mining based Path Estimation 15-745 Spring 2005

  5. Superblock Formation 15-745 Spring 2005

  6. Project Outline instrument instrumented program • Implement PMU simulator and Superblock optimization as SUIF passes • Implement Estimator offline using sampled branch profiles and SUIF CFG source label superblock c2dil optimized program path profile Offline estimator 15-745 Spring 2005

  7. Completed instrument instrumented program • PMU Simulation: modified HALT profiling lib • Initial offline estimator (?) source label superblock c2dil optimized program path profile Offline estimator 15-745 Spring 2005

  8. Initial Results 15-745 Spring 2005

  9. Todo instrument instrumented program • Superblock SUIF pass • Have c2dil build hyperblocks using superblocks • Refine path estimation heuristics source label superblock c2dil optimized program path profile Offline estimator 15-745 Spring 2005

  10. Questions or Comments? • Anyone have a good scheduler from Assignment 2? • Better scheduler = better comparison of superblock scheduling performance • The HALT lib maybe useful • If you need to uniquely label branches, basic blocks, loads, stores, etc. • Insert instrumentation at those points 15-745 Spring 2005

  11. Extra Slides 15-745 Spring 2005

  12. Related Work • Shye, et al. 2005 • Used heuristics to rebuild path profiles using PMU partial path samples • Achieved 80-99% path accuracy with <5% overhead • Did not evaluate impact on optimizations • Chen, et al. 2003 • Used PMU partial path sampling to dynamically form hot traces • Used to adapt to dynamic phase transitions 15-745 Spring 2005

More Related