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Title: Prometheus: Scalable and Accurate Emulation of Task-Based Applications on Many-Core Systems.

Modeling the performance of non-deterministic parallel applications on future many-core systems requires the development of novel simulation and emulation techniques and tools. We present “Prometheus”, a fast, accurate and modular emulation framework for task-based applications. By raising the level of abstraction and focusing on runtime synchronization, Prometheus can accurately predict applications’ performance on very large many-core systems. We validate our emulation framework against two real platforms (AMD Interlagos and Intel MIC) and report error rates generally below 4%. We, then, evaluate Prometheus’ performance and scalability: our results show that Prometheus can emulate a task-based application on a system with 512K cores in 11.5 hours. We present two test cases that show how Prometheus can be used to study the performance and behavior of systems that present some of the characteristics expected from exascale supercomputer nodes, such as active power management and processors with a high number of cores but reduced cache per core.
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Conference: IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS 2015), March 29-31, 2015, Philadelphia, PA, 308-317
Institute of Electrical and Electronic Engineers, New York, NY, United States(US).
Research Org:
Pacific Northwest National Laboratory (PNNL), Richland, WA (US)
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Country of Publication:
United States
Performance modeling; Task-based programming; exascale systems