Data-Flow/Dependence Profiling for Structured Transformations

被引：5
|
作者：
Gruber, Fabian [1 ]
Selva, Manuel [1 ]
Sampaio, Diogo [1 ]
Guillon, Christophe [2 ]
Moynault, Antoine [2 ]
Pouchet, Louis-Noel [3 ]
Rastello, Fabrice [1 ]
机构：
[1] Univ Grenoble Alpes, INRIA, CNRS, Grenoble INP,LIG, Grenoble, France
[2] STMicroelectronics, Geneva, Switzerland
[3] Colorado State Univ, Ft Collins, CO 80523 USA
来源：
PROCEEDINGS OF THE 24TH SYMPOSIUM ON PRINCIPLES AND PRACTICE OF PARALLEL PROGRAMMING (PPOPP '19) | 2019年
基金：
美国国家科学基金会;
关键词：
Performance Feedback; Polyhedral Model; Loop Tansformations; Compiler Optimization; Binary; Instrumentation; Dynamic Dependence Graph; DATA-DEPENDENCE; TOOLS;
D O I：
10.1145/3293883.3295737
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
Profiling feedback is an important technique used by developers for performance debugging, where it is usually used to pinpoint performance bottlenecks and also to find optimization opportunities. Assessing the validity and potential benefit of a program transformation requires accurate knowledge of the data flow and dependencies, which can be uncovered by profiling a particular execution of the program. In this work we develop poly-prof, an end-to-end infrastructure for dynamic binary analysis, which produces feedback about the potential to apply complex program rescheduling. Our tool can handle both inter- and intraprocedural aspects of the program in a unified way, thus providing interprocedural transformation feedback.
引用
收藏
页码：173 / 185
页数：13
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