DocumentCode :
2764727
Title :
A Memory Centric Kernel Framework for Accelerating Short-Range, Interactive Particle Simulation
Author :
Stewart, Ian ; Zhou, Shujia
Author_Institution :
Univ. of Maryland Baltimore County, Baltimore, MD, USA
fYear :
2010
fDate :
17-20 May 2010
Firstpage :
802
Lastpage :
807
Abstract :
To maximize the performance of emerging multi- and many-core accelerators such as the IBM Cell B.E. and the NVIDIA GPU, a Memory Centric Kernel Framework (MCKF) was developed. MCKF allows a user to decompose the physical space of an application based on the available fast memory in the accelerators. In this way, reducing the communication cost in accessing data can maximize the extraordinary computing power of the accelerators. MCKF is both generic and flexible because it encapsulates hardware-specific characteristics. It has been implemented and tested for short-range inter-active particle simulation on IBM Cell B.E. blades.
Keywords :
computer graphic equipment; digital simulation; parallel algorithms; storage management; IBM cell BE blades; MCKF; NVIDIA GPU; memory centric kernel framework; short-range inter-active particle simulation; Acceleration; Clouds; Computational modeling; Costs; Engines; Grid computing; Kernel; Memory management; Particle accelerators; Physics computing; GPU; IBM Cell B.E.; accelerator; kernel; memory management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cluster, Cloud and Grid Computing (CCGrid), 2010 10th IEEE/ACM International Conference on
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4244-6987-1
Type :
conf
DOI :
10.1109/CCGRID.2010.108
Filename :
5493381
Link To Document :
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