Optimally profiling and tracing programs
ACM Transactions on Programming Languages and Systems (TOPLAS)
Precise interprocedural dataflow analysis via graph reachability
POPL '95 Proceedings of the 22nd ACM SIGPLAN-SIGACT symposium on Principles of programming languages
PLDI '96 Proceedings of the ACM SIGPLAN 1996 conference on Programming language design and implementation
Proceedings of the 29th annual ACM/IEEE international symposium on Microarchitecture
Proceedings of the ACM SIGPLAN 1999 conference on Programming language design and implementation
Probabilistic data flow system with two-edge profiling
DYNAMO '00 Proceedings of the ACM SIGPLAN workshop on Dynamic and adaptive compilation and optimization
Timestamped whole program path representation and its applications
Proceedings of the ACM SIGPLAN 2001 conference on Programming language design and implementation
Flow Analysis of Computer Programs
Flow Analysis of Computer Programs
Interprocedural Path Profiling
CC '99 Proceedings of the 8th International Conference on Compiler Construction, Held as Part of the European Joint Conferences on the Theory and Practice of Software, ETAPS'99
A Novel Probabilistic Data Flow Framework
CC '01 Proceedings of the 10th International Conference on Compiler Construction
Path Matching in Compressed Control Flow Traces
DCC '02 Proceedings of the Data Compression Conference
Optimization of data prefetch helper threads with path-expression based statistical modeling
Proceedings of the 21st annual international conference on Supercomputing
Construction of speculative optimization algorithms
Programming and Computing Software
Probabilistic dataflow analysis using path profiles on structure graphs
Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering
| Hi-index | 0.00 |
Efficient use of machine resources in high-performance computer systems requires highly optimizing compilers with sophisticated analyses. Static analysis often fails to identify frequently executed portions of a program which are the places where optimizations achieve the greatest benefit.This paper introduces a novel data flow frequency analysis framework that computes the frequency with which a data flow fact will hold at some program point based on profiling information. Several approaches which approximate the frequencies based on k-edge profiling have been presented. However, no feasible approach for obtaining the accurate solution exists so far. Recently, efficient techniques for recording whole program paths (WPPs) have been developed. Our approach for computing data flow frequencies results in an accurate solution and utilizes WPPs to obtain the solution in reasonable time. In our experiments we show that the execution time of WPP-based frequency analysis is in case of the SPEC benchmark suite only a fraction of the overall compilation time.