Exploiting hardware performance counters with flow and context sensitive profiling
Proceedings of the ACM SIGPLAN 1997 conference on Programming language design and implementation
Gprof: A call graph execution profiler
SIGPLAN '82 Proceedings of the 1982 SIGPLAN symposium on Compiler construction
Fast, accurate call graph profiling
Software—Practice & Experience
Low-overhead call path profiling of unmodified, optimized code
Proceedings of the 19th annual international conference on Supercomputing
The Tau Parallel Performance System
International Journal of High Performance Computing Applications
Accurate, efficient, and adaptive calling context profiling
Proceedings of the 2006 ACM SIGPLAN conference on Programming language design and implementation
Valgrind: a framework for heavyweight dynamic binary instrumentation
Proceedings of the 2007 ACM SIGPLAN conference on Programming language design and implementation
Incremental call-path profiling: Research Articles
Concurrency and Computation: Practice & Experience - European–American Working Group on Automatic Performance Analysis (APART)
Proceedings of the 22nd annual ACM SIGPLAN conference on Object-oriented programming systems and applications
Binary analysis for measurement and attribution of program performance
Proceedings of the 2009 ACM SIGPLAN conference on Programming language design and implementation
Proceedings of the 33rd ACM SIGPLAN conference on Programming Language Design and Implementation
Cluster optimization and parallelization of simulations with dynamically adaptive grids
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
| Hi-index | 0.00 |
Profiling tools relate measurements to code context such as function names in order to guide code optimization. For a more detailed analysis, call path or phase-based profiling enhances the context by call chains or user defined phase names, respectively. In this paper, we propose argument controlled profiling as a new type of context extension using the value of function arguments as part of the context. For a showcase simulation code, we demonstrate that this simplifies and enriches the understanding and analysis of code--in particular recursive functions. Due to the new profiling technique, we found optimizations resulting in more than 16% runtime improvement. Argument controlled profiling is implemented as extension of Callgrind, a simulation-based profiling tool using runtime instrumentation.