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发表于 2009-5-19 22:38:35
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GPUGRID科学背景
http://www.gpugrid.net/science.php
Introduction
项目介绍
Features
特点
The main feature of GPUGRID is the brute force that it allows in terms of computational power by using accelerator processors, not only as an aggregate, but also as individual volunteered machines. This level of granularity is a fundamental requirement for all-atom molecular simulations as it permits to use a wide range of protocols on a very volatile grid. For instance, running MD on a single graphics device allows to execute trajectories of up to 4 ns/day on molecular system of 60,000 atoms. The practical way of use is therefore equivalent from a scientific perspective to that of a large personal supercomputer for molecular systems up to 100,000 atoms.
GPUGRID的主要特点是巨大的计算能力，它能获得由CUDA加速的GPU带来的计算能力，不仅仅是计算能力的聚合，更是志愿者个人计算机的聚合。要在一个快速变化的网格中使用宽松的判断准则，那么粒子级是全原子分子模拟的一项基本要求。例如，在一个单一的图形设备上运行分子动力学程序，分析一个由60000原子构成的分子系统的轨迹，每天只能模拟出4纳秒。在实际应用中，从科学的角度来看，相当于在一个大型个人超级计算机上模拟一个由10万原子构成的分子系统。
Goals
目标
We aim at performing all-atom high-throughput molecular dynamics simulations. In particular, using the large computational power, we are setting up adapted thermodynamic protocols which work on the underlying distributed infrastructure to compute free energies for protein-ligand and protein-protein interactions and conformational sampling. These quantities offer the possibility to support experimentation by a better understanding of the molecular mechanisms of interaction and to help biomedical research by providing a way for accurate virtual screening.
我们的目标是执行全原子高通量分子动力学的模拟。尤其是利用大型的计算能力，我们正在建立适应热力学原理的基本分布式计算基础设施，来计算自由能态的蛋白质配体、蛋白质之间的亲和力、筛选取样。这一切无不为更好的理解分子相互影响机制而做的实验提供了更多可能的支持，并能通过一种准确的虚拟筛选过程来促进生物医学研究的发展。 |
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发表于 2009-5-18 16:03:35
