Results 271 to 280 of about 48,067 (311)

GPUs and the Future of Parallel Computing

IEEE Micro, 2011
This article discusses the capabilities of state-of-the art GPU-based high-throughput computing systems and considers the challenges to scaling single-chip parallel-computing systems, highlighting high-impact areas that the computing research community can address.
Stephen W. Keckler, William J. Dally, Brucek Khailany, Michael Garland, David Glasco   +4 more
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Extending OpenSHMEM for GPU Computing

2013 IEEE 27th International Symposium on Parallel and Distributed Processing, 2013
Graphics Processing Units (GPUs) are becoming an integral part of modern supercomputer architectures due to their high compute density and performance per watt. In order to maximize utilization, it is imperative that applications running on these clusters have low synchronization and communication overheads.
Sreeram Potluri, Devendar Bureddy, Hao Wang 0002, Hari Subramoni, Dhabaleswar K. Panda 0001   +4 more
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Integral image computation on GPU

10th International Multi-Conferences on Systems, Signals & Devices 2013 (SSD13), 2013
In this paper we present an integral image algorithm that can run in real-time on a Graphics Processing Unit (GPU). Our system exploits the parallelisms in computation via the NVIDA CUDA programming model, which is a software platform for solving non-graphics problems in a massively parallel high performance fashion.
Marwa Chouchene, Fatma Ezahra Sayadi, Mohamed Atri, Rached Tourki   +3 more
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Count Sort for GPU Computing

2009 15th International Conference on Parallel and Distributed Systems, 2009
Counting sort is a simple, stable and efficient sort algorithm with linear running time, which is a fundamental building block for many applications. This paper depicts the design issues of a data parallel implementation of the count sort algorithm on a commodity multiprocessor GPU using the Compute Unified Device Architecture (CUDA) platform, both ...
Weidong Sun, Zongmin Ma 0001
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CPUs, GPUs, and Hybrid Computing

IEEE Micro, 2011
This introduction to the special issue discusses advances and challenges in the field of hybrid CPU/GPU computing.
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Sustainable GPU Computing at Scale

2011 14th IEEE International Conference on Computational Science and Engineering, 2011
General purpose GPU (GPGPU) computing has produced the fastest running supercomputers in the world. For continued sustainable progress, GPU computing at scale also need to address two open issues: a) how increase applications mean time between failures (MTBF) as we increase supercomputer's component counts, and b) how to minimize unnecessary energy ...
Justin Y. Shi, Moussa Taifi, Abdallah Khreishah, Jie Wu 0001   +3 more
openaire   +1 more source

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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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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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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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
openaire   +1 more source