Larrabee: a many-core x86 architecture for visual computing
ACM SIGGRAPH 2008 papers
General purpose molecular dynamics simulations fully implemented on graphics processing units
Journal of Computational Physics
GPU acceleration of cutoff pair potentials for molecular modeling applications
Proceedings of the 5th conference on Computing frontiers
Adapting a message-driven parallel application to GPU-accelerated clusters
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
SIAM Journal on Scientific Computing
369 Tflop-s molecular dynamics simulations on the petaflop hybrid supercomputer ‘Roadrunner’
Concurrency and Computation: Practice & Experience - Exploring the Frontiers of Computing Science and Technology: Adapting Emerging Multi-and Many-core Processors
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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.