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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 ...
Bill Dally
exaly +2 more sources
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 ...
Bill 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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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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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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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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Pension reserve computations on GPUs
Proceedings of the 3rd ACM SIGPLAN workshop on Functional high-performance computing, 2014New 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 +3 more
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Sustainable GPU Computing at Scale
2011 14th IEEE International Conference on Computational Science and Engineering, 2011General 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 +3 more
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