Predicting program behavior using real or estimated profiles
PLDI '91 Proceedings of the ACM SIGPLAN 1991 conference on Programming language design and implementation
Proceedings of the 29th annual ACM/IEEE international symposium on Microarchitecture
Performance solutions: a practical guide to creating responsive, scalable software
Performance solutions: a practical guide to creating responsive, scalable software
Workload characterization of emerging computer applications
Automatically characterizing large scale program behavior
Proceedings of the 10th international conference on Architectural support for programming languages and operating systems
Workload Design: Selecting Representative Program-Input Pairs
Proceedings of the 2002 International Conference on Parallel Architectures and Compilation Techniques
Predicting whole-program locality through reuse distance analysis
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
MiBench: A free, commercially representative embedded benchmark suite
WWC '01 Proceedings of the Workload Characterization, 2001. WWC-4. 2001 IEEE International Workshop
Measuring Benchmark Similarity Using Inherent Program Characteristics
IEEE Transactions on Computers
QEMU, a fast and portable dynamic translator
ATEC '05 Proceedings of the annual conference on USENIX Annual Technical Conference
Measuring Program Similarity: Experiments with SPEC CPU Benchmark Suites
ISPASS '05 Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2005
Discovering and Exploiting Program Phases
IEEE Micro
ISPASS '08 Proceedings of the ISPASS 2008 - IEEE International Symposium on Performance Analysis of Systems and software
MiDataSets: creating the conditions for a more realistic evaluation of Iterative optimization
HiPEAC'07 Proceedings of the 2nd international conference on High performance embedded architectures and compilers
Understanding performance modeling for modular mobile-cloud applications
ICPE '12 Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering
| Hi-index | 0.00 |
This paper introduces a new method to predict performance requirements of mobile devices' software tasks using system models describing the hardware and software. With the help of clustering algorithms and linear regression, behavioral models of software tasks are generated automatically. These models are used to project the runtime of representative parts of the software tasks. The runtime of representative execution parts is determined with instruction-accurate simulations which are not feasible for whole executions. The inputs for the projection task a model of the hardware platform and input data parameters, especially the data size. A major advantage of this approach is that the developers do not have to estimate the performance requirements themselves. In this way the method helps to seamlessly integrate the performance analysis process into the development process. The paper introduces the ideas in detail and presents an evaluation of the proposed method for typical software tasks of mobile devices.