Graphic Processor Units for Many-particle Dynamics
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NVIDIA is calling on global researchers to submit their innovations for the NVIDIA Global Impact Award - an annual grant of $150,000 for groundbreaking work that addresses the world's most important social and humanitarian problems.
With CUDA 6, we’re introducing one of the most dramatic programming model improvements in the history of the CUDA platform, Unified Memory. In a typical PC or cluster node today, the memories of the CPU and GPU are physically distinct and separated by the PCI-Express bus. Before CUDA 6, that is exactly how the programmer has to view things. Data that is shared between the CPU and GPU must be allocated in both memories, and explicitly copied between them by the program. This adds a lot of complexity to CUDA programs.
The NVIDIA® CUDA® Toolkit provides a comprehensive development environment for C and C++ developers building GPU-accelerated applications. The CUDA Toolkit includes a compiler for NVIDIA GPUs, math libraries, and tools for debugging and optimizing the performance of your applications. Additionally CUDA 5 introduces several new tools and features that make it easier than ever to add GPU acceleration to your applications.
It is my pleasure to announce that GPIUTMD is cited as a major molecular dynamic software in wikipedia.
The citations are listed as folllows:
also the software is cited in GPGPU.org
Simulations of Earth and space phenomena at NASA’s Goddard Space Flight Center are getting a boost from graphics processing units (GPUs). Early results on small laboratory GPU systems and a new GPU cluster at the NASA Center for Climate Simulation (NCCS) demonstrate potential for significant speedups versus conventional computer processors.
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NVIDIA is calling on global researchers to submit their innovations for the NVIDIA Global Impact Award - an annual grant of $150,000 for groundbreaking work that addresses the world's most important social and humanitarian problems.
Read more ...With CUDA 6, we’re introducing one of the most dramatic programming model improvements in the history of the CUDA platform, Unified Memory. In a typical PC or cluster node today, the memories of the CPU and GPU are physically distinct and separated by the PCI-Express bus. Before CUDA 6, that is exactly how the programmer has to view things. Data that is shared between the CPU and GPU must be allocated in both memories, and explicitly copied between them by the program. This adds a lot of complexity to CUDA programs.
Read more ...© 2009-2015 by GPIUTMD
Copyright © 2014. GPIUTMD - Graphic Processor Units for Many-particle Dynamics
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