Exploiting hardware advances for software testing and debugging (NIER track)
Proceedings of the 33rd International Conference on Software Engineering
Achieving application-centric performance targets via consolidation on multicores: myth or reality?
Proceedings of the 21st international symposium on High-Performance Parallel and Distributed Computing
THeME: a system for testing by hardware monitoring events
Proceedings of the 2012 International Symposium on Software Testing and Analysis
Reducing last level cache pollution in NUMA multicore systems for improving cache performance
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part III
Bandwidth bandit: quantitative characterization of memory contention
Proceedings of the 21st international conference on Parallel architectures and compilation techniques
How do developers use parallel libraries?
Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering
Parallelism profiling and wall-time prediction for multi-threaded applications
Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering
Reducing the energy cost of computing through efficient co-scheduling of parallel workloads
DATE '12 Proceedings of the Conference on Design, Automation and Test in Europe
ACM Transactions on Architecture and Code Optimization (TACO)
Exploiting multi-core nodes in peer-to-peer grids
Journal of Parallel and Distributed Computing
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For higher processing and computing power, chip multiprocessors (CMPs) have become the new mainstream architecture. This shift to CMPs has created many challenges for fully utilizing the power of multiple execution cores. One of these challenges is managing contention for shared resources. Most of the recent research address contention for shared resources by single-threaded applications. However, as CMPs scale up to many cores, the trend of application design has shifted towards multi-threaded programming and new parallel models to fully utilize the underlying hardware. There are differences between how single- and multi-threaded applications contend for shared resources. Therefore, to develop approaches to reduce shared resource contention for emerging multi-threaded applications, it is crucial to understand how their performances are affected by contention for a particular shared resource. In this research, we propose and evaluate a general methodology for characterizing multi-threaded applications by determining the effect of shared-resource contention on performance. To demonstrate the methodology, we characterize the applications in the widely used PARSEC benchmark suite for shared-memory resource contention. The characterization reveals several interesting aspects of the benchmark suite. Three of twelve PARSEC benchmarks exhibit no contention for cache resources. Nine of the benchmarks exhibit contention for the L2-cache. Of these nine, only three exhibit contention between their own threads-most contention is because of competition with a co-runner. Interestingly, contention for the Front Side Bus is a major factor with all but two of the benchmarks and degrades performance by more than 11%.