Analytical Modeling of Set-Associative Cache Behavior
IEEE Transactions on Computers
Improving online performance diagnosis by the use of historical performance data
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
Performance Engineering of Software Systems
Performance Engineering of Software Systems
SvPablo: A Multi-language Performance Analysis System
TOOLS '98 Proceedings of the 10th International Conference on Computer Performance Evaluation: Modelling Techniques and Tools
MDL: A Language And Compiler For Dynamic Program Instrumentation
PACT '97 Proceedings of the 1997 International Conference on Parallel Architectures and Compilation Techniques
Hi-index | 0.00 |
This paper presents a new technique that enhances the process and the methodology used in a performance prediction analysis. An automatic dynamic instrumentation methodology is added to Warwick's Performance Analysis and Characterization Environment PACE [1]. The automation process has eliminated the need to manually obtain application information and data. The Dynamic instrumentation has given PACE the ability to extract and utilize data that were hidden and unobtainable prior to execution. We give two examples to illustrate our methodology. While it was impossible to perform the analysis using the original method due to lack of essential information, the new technique successfully enabled PACE to conduct the prediction analysis in a dynamic environment. The results show that with the automated dynamic instrumentation, the performance prediction analysis of dynamic application execution is possible and the results obtained are reliable. We believe that the technique implemented here could eventually be used in other performance prediction tool-sets, and therefore enhance the ways in which the performance of systems and applications is analysed and predicted.