GPU-accelerated molecular modeling coming of age.
GPU-accelerated molecular modeling coming of age.
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DOI：
10.1016/j.jmgm.2010.06.010
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发表时间：
2010-09
影响因子：
2.9
通讯作者：
Schulten, Klaus
中科院分区：
文献类型：
--
作者：
Stone, John E.;Hardy, David J.;Ufimtsev, Ivan S.;Schulten, Klaus
传统上，图形处理单元(GPU)被用于分子建模，仅用于可视化分子结构和由分子动力学模拟产生的轨迹动画。现代GPU已经发展成完全可编程的大规模并行协处理器，现在可以利用它们来加速许多科学计算，通常比CPU代码提供大约一个数量级的加速，在特殊情况下提供两个数量级的加速。本文综述了利用GPU计算的分子建模算法的发展，已经取得的进展和有待解决的问题，以及有望对分子建模变得更加有用的GPU技术的持续发展。商用GPU的硬件加速预计将为桌面工作站带来万亿次浮点运算的性能，并在某些情况下潜在地将以前的批处理模式计算作业转变为交互任务，从而使整个计算生物学社区受益。
Graphics processing units (GPUs) have traditionally been used in molecular modeling solely for visualization of molecular structures and animation of trajectories resulting from molecular dynamics simulations. Modern GPUs have evolved into fully programmable, massively parallel co-processors that can now be exploited to accelerate many scientific computations, typically providing about one order of magnitude speedup over CPU code and in special cases providing speedups of two orders of magnitude. This paper surveys the development of molecular modeling algorithms that leverage GPU computing, the advances already made and remaining issues to be resolved, and the continuing evolution of GPU technology that promises to become even more useful to molecular modeling. Hardware acceleration with commodity GPUs is expected to benefit the overall computational biology community by bringing teraflops performance to desktop workstations and in some cases potentially changing what were formerly batch-mode computational jobs into interactive tasks.
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影响因子：
1.4
作者：
Hardy DJ;Stone JE;Schulten K
通讯作者：
Schulten K
影响因子：
4.4
作者：
ESSMANN, U;PERERA, L;PEDERSEN, LG
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影响因子：
3
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影响因子：
3.6
作者：
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通讯作者：
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影响因子：
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通讯作者：
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