Modern graphics processing units (GPUs) contain hundreds of arithmetic units and can be harnessed to provide tremendous acceleration for many numerically intensive scientific applications. The key to effective utilization of GPUs for scientific computing
Harte Zahlen zur Rechenleistung künftiger Nvidia-GPUs gab es jedoch nicht, die Einheit, in der Huangs Roadmap auf der Vertikalen skaliert ist "GFlops pro Watt". Wie der Nvidia-Mitbegründer betonte, ist die Rechenleistung nicht das Problem, sondern die "Power Wall". Schon mit den ersten Fermi-Grafikkarten kratzte Nvidia an der Grenze von 300 Watt.
provides a software development platform that allows developers to take advantage of a new generation of high performance processors. These new processors, including GPUs, the IBM Cell, and other multi-core processors
Marvin is a deep learning framework designed first and foremost to be hackable. It is naively simple for fast prototyping, uses only basic C/C++, and only calls CUDA and cuDNN as dependencies.
OpenVIDIA : GPU accelerated Computer Vision Library The OpenVIDIA project implements computer vision algorithms on computer graphics hardware, using OpenGL and Cg. The project provides useful example programs which run real time computer vision algorit
gpu.js is a single-file JavaScript library for GPGPU in the browser. gpu.js will automatically compile specially written JavaScript functions into shader language and run them on the GPU using the WebGL API. In the case where WebGL is not available, the functions will still run in regular JavaScript.
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X. Zhang, и Y. LeCun. (2015)cite arxiv:1502.01710Comment: This technical report is superseded by a paper entitled "Character-level Convolutional Networks for Text Classification", arXiv:1509.01626. It has considerably more experimental results and a rewritten introduction.