Results 231 to 240 of about 35,296 (265)

Throughput Computing on Future GPUs

2010
The focus on throughput and large data volumes separates Information Retrieval (IR) from scientific computing, since for IR it is critical to process large amounts of data efficiently, a task which the GPU currently does not excel at. Only recently has the IR community begun to explore the possibilities, and an implementation of a search engine for the
Rune J. Hovland, Anne C. Elster
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GPU Computing: The Future of Computing

Proceedings of the West Virginia Academy of Science, 2018
PARKER ANTHONY, Department of Computer Science, Mathematics, and Engineering, Shepherd University, Shepherdstown, WV, 25443.Computing requirements have grown over the last few years, bringing with it the benefits of complex computing. However, this had led to a bottleneck within the system.
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Pension reserve computations on GPUs

Proceedings of the 3rd ACM SIGPLAN workshop on Functional high-performance computing, 2014
New regulations from the European Union, called Solvency II, require that life insurance and pension providers perform more complicated calculations to demonstrate their solvency. At the same time, exploiting alternative computational paradigms such as GPGPU requires a high degree of expertise about the hardware and ties the computational ...
Christian Harrington, Nicolai Dahl, Peter Sestoft, David Raymond Christiansen   +3 more
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Efficient computation of histograms on the GPU

Proceedings of the 23rd Spring Conference on Computer Graphics, 2007
Recently, several image processing algorithms have been ported on the GPU because of its fast increase of performance. Some of these algorithms need to compute a histogram, but the computation of the histogram is not well supported on the GPU because of its architecture.
Alexander Kubias, Frank Deinzer, Matthias Kreiser, Dietrich Paulus   +3 more
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Geospatial overlay computation on the GPU

Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2011
General purpose computing on graphics processing units provides a relatively low cost mechanism to achieve high computational throughput on desktop computers. However, the architecture of GPUs is fundamentally different than CPUs; thus, traditional algorithms cannot simply be run on a GPU.
Mark McKenney, Gabriel De Luna, Schiller Hill, Logan Lowell   +3 more
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Adding GPU Computing to Computer Organization Courses

2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum, 2013
How can parallel computing topics be incorporated into core courses that are taken by the majority of undergraduate students? This paper reports our experiences adding GPU computing with CUDA into the core undergraduate computer organization course at two different colleges.
David P. Bunde, Karen L. Karavanic, Jens Mache, Christopher T. Mitchell   +3 more
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Mapping computational concepts to GPUs

ACM SIGGRAPH 2005 Courses on - SIGGRAPH '05, 2005
Recently, graphics processors have emerged as a powerful computational platform. A variety of encouraging results, mostly from researchers using GPUs to accelerate scientific computing and visualization applications, have shown that significant speedups can be achieved by applying GPUs to data-parallel computational problems.
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GPU‐accelerated computation of electron transfer

Journal of Computational Chemistry, 2012
AbstractElectron transfer is a fundamental process that can be studied with the help of computer simulation. The underlying quantum mechanical description renders the problem a computationally intensive application. In this study, we probe the graphics processing unit (GPU) for suitability to this type of problem.
HOEFINGER, SIEGFRIED, ACOCELLA, ANGELA, Pop S. C., Narumi T., Yasuoka K., Beu T., ZERBETTO, FRANCESCO   +6 more
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The GPU enters computing's mainstream

Computer, 2003
The Siggraph/Eurographics Graphics Hardware 2003 workshop, held in San Diego, will likely be remembered as a turning point in modern computing. In one of those rare moments when a new paradigm visibly begins changing general-purpose computing's course, what has traditionally been a graphics-centric workshop shifted its attention to the nongraphics ...
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GPU Computing for Compute-Intensive Scientific Calculation

2019
GPU has emerged as a platform that off-loads computation intensive work from CPU and performs numerical computations in less time. One such mathematical operation is matrix multiplication. Matrix is one of the fundamental mathematical objects used in the scientific calculation, with applicability in various fields such as computer graphics, analysis of
Sandhya Parasnath Dubey, M. Sathish Kumar, S. Balaji 0003   +2 more
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