Compilers: principles, techniques, and tools
Compilers: principles, techniques, and tools
Dynamic control of performance monitoring on large scale parallel systems
ICS '93 Proceedings of the 7th international conference on Supercomputing
ATOM: a system for building customized program analysis tools
PLDI '94 Proceedings of the ACM SIGPLAN 1994 conference on Programming language design and implementation
EEL: machine-independent executable editing
PLDI '95 Proceedings of the ACM SIGPLAN 1995 conference on Programming language design and implementation
Advanced compiler design and implementation
Advanced compiler design and implementation
Improving online performance diagnosis by the use of historical performance data
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
A fast algorithm for finding dominators in a flowgraph
ACM Transactions on Programming Languages and Systems (TOPLAS)
Capturing and automating performance diagnosis: the Poirot approach
IPPS '95 Proceedings of the 9th International Symposium on Parallel Processing
Deep Start: A Hybrid Strategy for Automated Performance Problem Searches
Euro-Par '02 Proceedings of the 8th International Euro-Par Conference on Parallel Processing
A Rule-based Approach for Automatic Bottleneck Detection in Programs on Shared
HIPS '97 Proceedings of the 1997 Workshop on High-Level Programming Models and Supportive Environments (HIPS '97)
FINESSE: a prototype feedback-guided performance enhancement system
EURO-PDP'00 Proceedings of the 8th Euromicro conference on Parallel and distributed processing
| Hi-index | 0.01 |
Automated online search is a powerful technique for performance diagnosis. Such a search can change the types of experiments it performs while the program is running, making decisions based on live performance data. Previous research has addressed search speed and scaling searches to large codes and many nodes. This paper explores using a finer granularity for the bottlenecks that we locate in an automated online search, i.e., refining the search to bottlenecks localized to loops. The ability to insert and remove instrumentation on-the-fly means an online search can utilize fine-grain program structure in ways that are infeasible using other performance diagnosis techniques. We automatically detect loops in a program’s binary control flow graph and use this information to efficiently instrument loops. We implemented our new strategy in an existing automated online performance tool, Paradyn. Results for several sequential and parallel applications show that a loop-aware search strategy can increase bottleneck precision without compromising search time or cost.