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Managing multi-configuration hardware via dynamic working set analysis
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Automatically characterizing large scale program behavior
Proceedings of the 10th international conference on Architectural support for programming languages and operating systems
Wavelets for Computer Graphics: A Primer, Part 1
IEEE Computer Graphics and Applications
Integrating Adaptive On-Chip Storage Structures for Reduced Dynamic Power
Proceedings of the 2002 International Conference on Parallel Architectures and Compilation Techniques
Vacuum packing: extracting hardware-detected program phases for post-link optimization
Proceedings of the 35th annual ACM/IEEE international symposium on Microarchitecture
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
Runtime Power Monitoring in High-End Processors: Methodology and Empirical Data
Proceedings of the 36th annual IEEE/ACM International Symposium on Microarchitecture
Text Detection in Images Based on Unsupervised Classification of High-Frequency Wavelet Coefficients
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
ASPLOS XI Proceedings of the 11th international conference on Architectural support for programming languages and operating systems
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Pin: building customized program analysis tools with dynamic instrumentation
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Dynamic detection and visualization of software phases
WODA '05 Proceedings of the third international workshop on Dynamic analysis
Dynamic phase analysis for cycle-close trace generation
CODES+ISSS '05 Proceedings of the 3rd IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Region Monitoring for Local Phase Detection in Dynamic Optimization Systems
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Structures for phase classification
ISPASS '04 Proceedings of the 2004 IEEE International Symposium on Performance Analysis of Systems and Software
Fast, Accurate Microarchitecture Simulation Using Statistical Phase Detection
ISPASS '05 Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2005
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ISPASS '05 Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2005
Discovering and Exploiting Program Phases
IEEE Micro
Texture segmentation using hierarchical wavelet decomposition
Pattern Recognition
Predicting locality phases for dynamic memory optimization
Journal of Parallel and Distributed Computing
Automatic analysis of speedup of MPI applications
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Scalable load-balance measurement for SPMD codes
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
Evaluating similarity-based trace reduction techniques for scalable performance analysis
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Phase complexity surfaces: characterizing time-varying program behavior
HiPEAC'08 Proceedings of the 3rd international conference on High performance embedded architectures and compilers
Automatic Phase Detection and Structure Extraction of MPI Applications
International Journal of High Performance Computing Applications
Journal of Parallel and Distributed Computing
Characterizing time-varying program behavior using phase complexity surfaces
Transactions on High-Performance Embedded Architectures and Compilers IV
Improving dynamic prediction accuracy through multi-level phase analysis
Proceedings of the 13th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, Tools and Theory for Embedded Systems
Extracting the optimal sampling frequency of applications using spectral analysis
Concurrency and Computation: Practice & Experience
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Phase analysis has proven to be a useful method of summarizing the time-varying behavior of programs, with uses ranging from reducing simulation time to guiding run-time optimizations. Although phase classification techniques based on basic block vectors have shown impressive accuracies on SPEC benchmarks, commercial programs remain a significant challenge due to their complex behaviors and multiple threads. Some behaviors, such as L2 cache misses, may have less correlation with the code and therefore are much harder to capture with basic block frequency vectors.Comparing the similarity of two or more intervals requires a good metric, one that is not only fast enough to analyze the full execution of the program, but that is also highly correlated with important performance degrading events (such as L2 misses). We examine the use of many different interval similarity metrics and their uses for program phase analysis across a range of commercial applications and show that there is still significant room for improvement. To address this problem, we introduce a novel wavelet-based phase classification scheme that captures and compares images of memory behavior in two or more dimensions. Over a set of five commercial applications, we show that a wavelet-based scheme can strictly outperform a broad range of prior metrics both in terms of accuracy and overhead.