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A Memory Centric Kernel Framework for Accelerating Short-Range, Interactive Particle Simulation

Ian Stewart, Shujia Zhou
Univ. of Maryland Baltimore County, Baltimore, MD, USA
10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (CCGrid), 2010

@inproceedings{stewart2010memory,

   title={A Memory Centric Kernel Framework for Accelerating Short-Range, Interactive Particle Simulation},

   author={Stewart, I. and Zhou, S.},

   booktitle={2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing},

   pages={802–807},

   year={2010},

   organization={IEEE}

}

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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.
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