Automatically characterizing large scale program behavior
Proceedings of the 10th international conference on Architectural support for programming languages and operating systems
Basic Block Distribution Analysis to Find Periodic Behavior and Simulation Points in Applications
Proceedings of the 2001 International Conference on Parallel Architectures and Compilation Techniques
Proceedings of the 30th annual international symposium on Computer architecture
Characterizing and Predicting Program Behavior and its Variability
Proceedings of the 12th International Conference on Parallel Architectures and Compilation Techniques
Exploiting program execution phases to trade power and performance for media workload
Proceedings of the 2004 Asia and South Pacific Design Automation Conference
Web Server Software Architectures
IEEE Internet Computing
Solaris Internals (2nd Edition)
Solaris Internals (2nd Edition)
Examining performance differences in workload execution phases
WWC '01 Proceedings of the Workload Characterization, 2001. WWC-4. 2001 IEEE International Workshop
Structures for phase classification
ISPASS '04 Proceedings of the 2004 IEEE International Symposium on Performance Analysis of Systems and Software
Defining relevant distances between server workloads
Performance Evaluation
Hi-index | 0.00 |
This technical report explores workload characterization using processor hardware counter sampling. We assume that we are measuring more hardware counter events than the number of physical counters on the processor, i.e., the counters are set to measure different events after every measurement. We characterize workloads on typical timescales between 5 and 30 minutes, with different phasing properties. We evaluate two competing strategies, a short sample time strategy designed to minimize overhead and a long sample time strategy designed to get better averaging. We find that both strategies are likely to produce accurate results, independent of underlying workload phasing, but neither strategy is ideal. We find that the optimal strategy is a fairly short sample time combined with continuous iteration over the counter set.