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O AK R IDGE N ATIONAL L ABORATORY U. S. D EPARTMENT OF E NERGY 1 A Brief Summer Recap Flocking, CUDA, GPU, Ants, and More Jesse St.Charles
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O AK R IDGE N ATIONAL L ABORATORY U. S. D EPARTMENT OF E NERGY 2 Some Terms: Kernel – A algorithm which executes on the GPU (blueprint for all simultaneous threads) Host – CPU (normal location programs run) Device – Graphics Card (this is the location of the GPU) CUDA – Compute Unified Device Architecture (API that allows programming of the GPU) made by NVIDIA
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O AK R IDGE N ATIONAL L ABORATORY U. S. D EPARTMENT OF E NERGY 3 NVIDIA CUDA Single Program Multiple Data architecture (SPMD) Uses Grid/Block thread spawning Programmer uses thread ID and block ID to access unique data per thread
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O AK R IDGE N ATIONAL L ABORATORY U. S. D EPARTMENT OF E NERGY 4 CUDA: Flocking and Document Flocking Main() Kernel Call-> Main() Kernel Call-> Main One Loop Per Generation Neighborhood Calculation Kernel and Document Comparison Update Pos and Velocity Kernel Start N2N2 N Threads
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O AK R IDGE N ATIONAL L ABORATORY U. S. D EPARTMENT OF E NERGY 5 Initial Flocking Results GPU CPU 100x
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O AK R IDGE N ATIONAL L ABORATORY U. S. D EPARTMENT OF E NERGY 6 Document Flocking Results CPU GPU 5x
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O AK R IDGE N ATIONAL L ABORATORY U. S. D EPARTMENT OF E NERGY 7 Document Flocking Results Document comparisons – most expensive 2000 Documents at Generation: 2 52 200
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O AK R IDGE N ATIONAL L ABORATORY U. S. D EPARTMENT OF E NERGY 8
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O AK R IDGE N ATIONAL L ABORATORY U. S. D EPARTMENT OF E NERGY 9 Other Summer Work Shortest Path Done for traffic simulation and emergency response Produced an Ant-Colony shortest path implementation on the GPU but had convergence issues when the graph became to large Implemented Dijkstra’s shortest path algorithm on the GPU; no clear benefit on the GPU
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O AK R IDGE N ATIONAL L ABORATORY U. S. D EPARTMENT OF E NERGY 10 Summer End Products Ant-Colony shortest path GPU program Dijkstra’s Shortest path GPU program Document Flocking GPU program with display Companion CPU implementations Paper produced and submitted for publication Poster produced for presentation
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O AK R IDGE N ATIONAL L ABORATORY U. S. D EPARTMENT OF E NERGY 11 Future Work in Document Flocking Use dimensionality reduction Develop document refinement GPU implementation that removes stop words, stems, and calculates TF-ICF Develop a whole document analysis system for a GPU workstation (one GPU for refinement, one for document clustering) Find F-measure for flocking cluster accuracy
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O AK R IDGE N ATIONAL L ABORATORY U. S. D EPARTMENT OF E NERGY 12 My Immediate Future Fall 2007 Last undergraduate semester at UTC Continuing research collaboration with Xiaohui Applying for graduate fellowships Selecting and applying to Graduate CS programs to begin PhD track in Fall 2008
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