Results 261 to 270 of about 48,067 (311)
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IEEE Micro, 2010
GPU computing is at a tipping point, becoming more widely used in demanding consumer applications and high-performance computing. This article describes the rapid evolution of GPU architectures-from graphics processors to massively parallel many-core multiprocessors, recent developments in GPU computing architectures, and how the enthusiastic adoption ...
William J Dally
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GPU computing is at a tipping point, becoming more widely used in demanding consumer applications and high-performance computing. This article describes the rapid evolution of GPU architectures-from graphics processors to massively parallel many-core multiprocessors, recent developments in GPU computing architectures, and how the enthusiastic adoption ...
William J Dally
exaly +2 more sources
ACM SIGGRAPH 2006 Research posters on - SIGGRAPH '06, 2006
Due to the immense computational power of today’s graphics processors (GPU), general purpose computation on GPUs has become a vivid research area. The performance of algorithms running on GPUs highly depends on how well they can be arranged to fit and exploit the processors single instruction multiple data (SIMD) architecture.
Oliver Fluck +3 more
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Due to the immense computational power of today’s graphics processors (GPU), general purpose computation on GPUs has become a vivid research area. The performance of algorithms running on GPUs highly depends on how well they can be arranged to fit and exploit the processors single instruction multiple data (SIMD) architecture.
Oliver Fluck +3 more
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Using GPU Computing for Solving the Two-Dimensional Guillotine Cutting Problem
INFORMS Journal on Computing, 2016 In recent years, GPU computing has become an increasingly important tool to develop efficient applications in several areas, including optimization.
Marco A Boschetti +2 more
exaly +2 more sources
Fault Table Computation on GPUs
Journal of Electronic Testing, 2010In this paper, we explore the implementation of fault table generation on a Graphics Processing Unit (GPU). A fault table is essential for fault diagnosis and fault detection in VLSI testing and debug. Generating a fault table requires extensive fault simulation, with no fault dropping, and is extremely expensive from a computational standpoint.
Kanupriya Gulati, Sunil P. Khatri
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A GPU Implementation of the ASP Computation
2016General Purpose Graphical Processing Units (GPUs) are affordable multi-core platforms, providing access to large number of cores, but at the price of a complex architecture with non-trivial synchronization and communication costs. This paper presents the design and implementation of a conflict-driven ASP solver, that is capable of exploiting the ...
Agostino Dovier +3 more
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Communications of the ACM, 2016
Graphical processing units have emerged as a major powerhouse in the computing world, unleashing huge advancements in deep learning and AI.
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Graphical processing units have emerged as a major powerhouse in the computing world, unleashing huge advancements in deep learning and AI.
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Scientific Computing with GPUs
Computing in Science & Engineering, 2012This special issue attests to the widespread use of GPUs in the scientific computing community. Here the guest editor discusses the articles selected for this issue, and considers how they represent the range of possibilities (and risks) for using GPUs in scientific applications.
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2010
The success of the gaming industry is now pushing processor technology like we have never seen before. Since recent graphics processors (GPU's) have been improving both their programmability as well as have been adding more and more floating point processing, it makes them very appealing as accelerators for general-purpose computing. This minisymposium
Anne C. Elster, Stéphane Requena
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The success of the gaming industry is now pushing processor technology like we have never seen before. Since recent graphics processors (GPU's) have been improving both their programmability as well as have been adding more and more floating point processing, it makes them very appealing as accelerators for general-purpose computing. This minisymposium
Anne C. Elster, Stéphane Requena
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SIGGRAPH Asia 2013 Courses, 2013
Modern GPUs support more flexible programming models through systems such as DirectCompute, OpenGL compute, OpenCL, and CUDA. Although much has been made of GPGPU programming, this course focuses on the application of compute on GPUs for graphics in particular.We will start with a brief overview of the underlying GPU architectures for compute.
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Modern GPUs support more flexible programming models through systems such as DirectCompute, OpenGL compute, OpenCL, and CUDA. Although much has been made of GPGPU programming, this course focuses on the application of compute on GPUs for graphics in particular.We will start with a brief overview of the underlying GPU architectures for compute.
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Automating GPU computing in MATLAB
Proceedings of the international conference on Supercomputing, 2011MATLAB is a popular software platform for scientific and engineering software writers. It offers a high level of abstraction for fundamental mathematical operations and extensive highly optimized domain-specific libraries for several scientific and engineering disciplines. With the recent availability of GPU libraries for MATLAB, it has become possible
Chun-Yu Shei +2 more
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