NDLI: A Hardware-Driven Profiling Scheme for Identifying Program Hot Spots to Support Runtime Optimization (1999)

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A Hardware-Driven Profiling Scheme for Identifying Program Hot Spots to Support Runtime Optimization (1999)

Content Provider	CiteSeerX
Author	Merten, Matthew Trick, Andrew R. George, Christopher N. Gyllenhaal, John C. Hwu, Wen-Mei W.
Description	in Proceedings of the 26th Annual International Symposium on Computer Architecture This paper presents a novel hardware-based approach for identifying, profiling, and monitoring hot spots in order to support runtime optimization of generalpurpose programs. The proposed approach consists of a set of tightly coupled hardware tables and control logic modules that are placed in the retirement stage of a processor pipeline removed from the critical path. The features of the proposed design include rapid detection of program hot spots after changes in execution behavior, runtime-tunable selection criteria for hot spot detection, and negligible overhead during application execution. Experiments using several SPEC95 benchmarks, as well as several large WindowsNT applications, demonstrate the promise of the proposed design. 1 Introduction Optimizing compilers can gain significant performance benefits by performing code transformations based on a program's runtime profile. Traditionally, profiles are collected by running an instrumented version of the executable. However, bec...
File Format	PDF
Language	English
Publisher Date	1999-01-01
Access Restriction	Open
Subject Keyword	Support Runtime Optimization Code Transformation Instrumented Version Negligible Overhead Generalpurpose Program Runtime Profile Retirement Stage Critical Path Hardware Table Novel Hardware-based Approach Application Execution Hardware-driven Profiling Scheme Hot Spot Detection Processor Pipeline Hot Spot Runtime-tunable Selection Criterion Program Hot Spot Runtime Optimization Execution Behavior Significant Performance Benefit Several Large Windowsnt Application Several Spec95 Benchmark Logic Module Rapid Detection
Content Type	Text
Resource Type	Article

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