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EPM 2010 : PDPTA - Experimental Performance Measurements on Multi- and Many-core systems


When Jul 13, 2010 - Jul 15, 2010
Where Las Vegas
Submission Deadline Mar 5, 2010
Notification Due Apr 1, 2010
Final Version Due Apr 22, 2010

Call For Papers

Session on Experimental Performance Measurements on Multi- and Many-core systems

Within the 2010 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA'10) Las Vegas, Nevada, USA. 13-15 July 2010

In a few years multi- and many-core processors will not just have 8, 12 or 16 cores, but many more. At the same time will the ecosystem of applications making advanced use of those architectures keep inflating at a rapid pace on supercomputers, game consoles, clusters, servers, workstations, and laptops. In this emerging combinatorial universe of architectures and applications running to a large extent in commercial environments with mixes of closed and open source systems and applications, there is a need for alternative evaluation methods to compliment e.g. code analysis and operating systems modifications.

Authors are invited to submit manuscripts that present original research in the area of experimental performance measurements. The name of the session mentions multi- and many-cores but all experimental methods are of interest, whether they are performed on a single core, cluster or a massive multiprocessor. Work focusing real world commercial situations/environments and/or emerging technologies are especially welcome.

Topics of interest include, but are not limited to:
- Benchmarking on multi-core architectures
- Bottleneck detection techniques in e.g. industrial HPC-environments/applications
- Performance evaluation with limited code and/or system access
- Experiments, evaluations or modeling of application behavior
- Experimental predictions of application behavior and estimates of approximation errors.
- Evaluations or modeling of application behavior in competitive conditions for resources (e.g. two or more applications sharing cores, memory, network, etc.)
- Tools, techniques and methods to perform experiments and analyze results/optimal
Usage of experimental data in real world HPC environments, e.g. use in scheduling etc.

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