ENHANCE - Enabling heterogeneous hardware acceleration using novel programming and scheduling models
ENHANCE aims on a better integration and simplified usage of heterogeneous computing resources within current and upcoming computing systems.
Heterogeneous systems contain multiple compute components like multi-core processors, complemented by graphics processing units (GPUs) and/or field programmable gate arrays (FPGAs). Employing such hardware architectures raises several challenges in programmability, performance estimation and scheduling that are approached within the ENHANCE project and shall result in a framework enabling the development and use of applications on heterogeneous systems. The benefit of the developed methods for the industrial application partners is of special importance.
Further details:
http://www.enhance-project.de/
Publikationen
2014
2013
2012
2014 |
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Sebastian Dreßler, Thomas Steinke | An Automated Approach for Estimating the Memory Footprint of Non-linear Data Objects | Euro-Par 2013: Parallel Processing Workshops, pp. 249-258, Vol.8374, Lecture Notes in Computer Science, 2014 (preprint available as ) |
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2013 |
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Sebastian Dreßler, Thomas Steinke | Automated Analysis of Complex Data Objects | 28th International Supercomputing Conference, ISC 2013, Leipzig, Germany, June 16-20, 2013, 2013 |
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F. Ries, M. Ditze, A. Piater, E. Singer, V. Fäßler, Sebastian Dreßler, T. Soddemann | Tool-Supported Integration of Hardware Acceleration in Automotive CFD-Simulations | NAFEMS 2013 Proceedings, 2013 |
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2012 |
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Sebastian Dreßler, Thomas Steinke | A Novel Hybrid Approach to Automatically Determine Kernel Interface Data Volumes | ZIB-Report 12-23 |
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Sebastian Dreßler, Thomas Steinke | Energy consumption of CUDA kernels with varying thread topology | Computer Science - Research and Development, pp. 1-9, 2012 |
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Florian Wende, Frank Cordes, Thomas Steinke | On Improving the Performance of Multi-threaded CUDA Applications with Concurrent Kernel Execution by Kernel Reordering | Application Accelerators in High Performance Computing (SAAHPC), 2012 Symposium on, pp. 74-83, 2012 |
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