Using compiler-generated approximate critical path information to prioritise instructions for value prediction.

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
Read More Add to Saved list
  • Author(s): Zhao, Q.; Lilja, D.J.
  • Source:
    IEE Proceedings -- Computers & Digital Techniques. Sep2004, Vol. 151 Issue 5, p321-331. 11p.
  • Additional Information
    • Subject Terms:
      ALGORITHMS; COMPILERS (Computer programs); SYSTEMS software; COMPUTER input-output equipment; CRITICAL path analysis; COMPUTER software
    • Abstract:
      One of the potential difficulties in developing cost-effective value prediction mechanisms is determining which instructions should be selected for prediction when the hardware resources are limited. The authors examine a compiler algorithm that statically assigns priorities to instructions using approximate critical path information to identify the best candidates for value prediction. This static priority information is encoded into the instructions and subsequently used by the hardware to choose the most critical instructions at run-time for value prediction. The algorithm is implemented in the GCC compiler and performance potential is evaluated using an extended version of the SimpleScalar processor simulator. Our results with the SPEC95 and SPEC2000 benchmark programs show that this approximate algorithm can effectively capture the critical path information to consistently improve the performance of a processor with a hybrid value predictor compared to using no information about the criticality of instructions. Furthermore, it is shown that using only four priority levels encoded into two instruction bits is sufficient to capture enough priority information to effectively use the value prediction hardware. [ABSTRACT FROM AUTHOR]
    • Abstract:
      Copyright of IEE Proceedings -- Computers & Digital Techniques is the property of Institution of Engineering & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)