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
Use a computer? Game on a PC? Ever wonder how those graphics get so pretty? Let's go inside your high-end graphics card with this animation. Subscribe for mo...
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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“The GPU is a powerful, programmable platform that is perfect for computing applications such as seismic processing for oil and gas exploration, computing in bioscience, and financial modeling,” says Andy Keane, general manager of the GPU computing business at NVIDIA, a pioneer in using GPUs for HPC. “The GPU will change the way engineers and researchers approach these problems.”
contains over 40 chapters and nearly 1000 pages full of the latest GPU programming techniques, and includes hundreds of full-color diagrams and pictures. GPU Gems 3 won the Game Developer Magazine's 2007 Front Line Award. Aailable for free online on the NVIDIA Developer Site
With the increasing programmability of commodity graphics processing units (GPUs), these chips are capable of performing more than the specific graphics computations for which they were designed.
Data Mining, Analytics, and Databases
Databases are the workhorse of the enterprise today. Searching through databases and finding useful information has become a big computational challenge. Researchers from academia and Microsoft, Oracle, SAP, and many other corporations are looking to CUDA-enabled GPUs to find a scalable solution.
CUDA lets you work with familiar programming concepts while developing software that can run on a GP This is the first of a series of articles to introduce you to the power of CUDA -- through working code -- and to the thought process to help you map applications onto multi-threaded hardware (such as GPUs) to get big performance increases. Of course, not all problems can be mapped efficiently onto multi-threaded hardware, so part of my thought process will be to distinguish what will and what won't work, plus provide a common-sense idea of what might work "well-enough". "CUDA programming" and "GPGPU programming" are not the same (although CUDA runs on GPUs). CUDA permits working with familiar programming concepts while developing software that can run on a GPU. It also avoids the performance overhead of graphics layer APIs by compiling your software directly to the hardware (GPU assembly language, for instance), thereby providing great performance.
R. Okuta, Y. Unno, D. Nishino, S. Hido, und C. Loomis. Proceedings of Workshop on Machine Learning Systems (LearningSys) in The Thirty-first Annual Conference on Neural Information Processing Systems (NIPS), (2017)