ABI: Development: Parallel Computing for Phylogenetics: Grid, Public and GPU Computing

马里兰大学学院公园分校获得了一笔资助，用于支持网络基础设施的发展，该基础设施将通过使用几种并行计算方法来促进、加速和提高推断生物体之间进化关系的能力。其中心思想是在多个不同层次的并行计算的基础上建立和扩展以前的工作，以便更好地利用各种计算资源，特别是通过志愿计算提供的现有桌面处理能力。主要产品将是一个增强的网格计算系统，为系统进化树搜索定制，并可通过用户友好的网络界面访问，连接全球数千台个人计算机。该项目将改善台式计算机内部第二种未充分利用的资源的使用，即图形卡和其他通常不用于正常数据处理的处理器，它可以比中央处理器（cpu）更快地进行许多科学计算。一个免费的、开源的并行最大似然计算库将被扩展。公共计算为公众有意义地参与科学研究提供了一种机制。来自143个国家的近17000人自愿使用他们的计算机，并通过当前的系统进行进化分析。随着项目发展的进一步努力，志愿者的数量预计会增加。这种计算模式不仅提高了科学研究的速度和质量，而且更节能。此外，该项目还提供了让学生和其他人参与并行和公共计算研究的机会。该项目的结果将通过PI的网站http://openevolution.org和http://lattice.umiacs.umd.edu进行访问。

The University of Maryland College Park is awarded a grant to support the development of cyberinfrastructure that will facilitate, accelerate, and improve the ability to infer evolutionary relationships among organisms through the use of several types of parallel computing methods. The central idea is to build upon and extend previous work at multiple different levels of parallel computing to better take advantage of a diversity of computing resources, particularly existing desktop processing capacity available through volunteer computing. The main product will be an enhanced grid computing system, customized for phylogenetic tree search and accessible through a user-friendly web interface, that links thousands of individual computers worldwide. The project will improve use of a second underutilized resource inside desktop computers, namely graphics cards and other types of processors not usually used for normal data processing, which can do many scientific calculations faster than the central processing unit (cpu). A free, open-source library for parallelized maximum likelihood calculations will be extended.Public computing provides a mechanism for meaningful public involvement in scientific research. Almost 17,000 people in 143 countries have volunteered use of their computers and have run evolutionary analyses through the current system. With additional project development effort, the number of volunteers is expected to increase. This model of computing not only increases the speed and quality of scientific research, but is also more energy efficient. Furthermore, the project provides opportunities to involve students and others in parallel and public computing research. Results of this project will be accessible via the PI's websites at http://openevolution.org and http://lattice.umiacs.umd.edu.