GPU acceleration of cutoff pair potentials for molecular modeling applications
Proceedings of the 5th conference on Computing frontiers
Stream processing for fast and efficient rotated Haar-like features using rotated integral images
International Journal of Intelligent Systems Technologies and Applications
Rigel: an architecture and scalable programming interface for a 1000-core accelerator
Proceedings of the 36th annual international symposium on Computer architecture
Performance Optimization Strategies of High Performance Computing on GPU
APPT '09 Proceedings of the 8th International Symposium on Advanced Parallel Processing Technologies
Accelerating the MilkyWay@Home volunteer computing project with GPUs
PPAM'09 Proceedings of the 8th international conference on Parallel processing and applied mathematics: Part I
Simple optimizations for an applicative array language for graphics processors
Proceedings of the sixth workshop on Declarative aspects of multicore programming
Journal of Computational Physics
Recent progress and challenges in exploiting graphics processors in computational fluid dynamics
The Journal of Supercomputing
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Commercial graphics processors (GPUs) have high compute capacity at very low cost, which makes them attractive for general purpose scientic computing. In this poster we show how graphics processors can be used for N-body simulations to obtain large improvements in performance over current generation CPUs. We have developed a highly optimized algorithm for performing the O(N^2) force calculations that constitute the major part of stellar and molecular dynamics simulations. In the calculations, we achieve sustained performance of nearly 100 GFlops on an ATI X1900XTX. The performance on GPUs 25x an Intel Pentium4, and 2x specialized hardware such as GRAPE-6A, but at a fraction of the cost. Furthermore, the wide availability of GPUs has signicant implications for cluster computing and distributed computing efforts like Folding@Home.