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