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.
- Publication Date:
- OSTI Identifier:
- Report Number(s):
- DOE Contract Number:
- Resource Type:
- Resource Relation:
- 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)
- Sponsoring Org:
- Country of Publication:
- United States
- Performance modeling; Task-based programming; exascale systems