Development of Advanced Computer Hardware and Software

随着可用于大规模科学计算的并行计算机资源的增加，优化这些资源的使用是必不可少的。这些努力包括开发适用于大分子模拟的并行计算技术，以及开发用于低成本高效率模拟的并行计算机集群和相关软件。目前的项目包括：- LoBoS；使用PC集群的高性能计算-并行QM/MM方法的开发- PC集群生物信息学工具的开发-分子动力学并行算法的开发和评估-并行CHARMM的开发和支持-并行计算的延迟容忍算法的开发LoBoS (Lots of Boxes on Shelves), LoBoSII（以及即将发布的LoBoSIII/Biowulf II）超级计算机已经使用商用PC设计和构建。与传统超级计算机供应商提供的产品相比，它们在价格/性能方面提供了10倍以上的改进。对于具有128个处理器和每个节点多个快速以太网连接的某些应用程序，lobo采用的初始方法非常成功。LoBoSII在可伸缩性方面有了实质性的改进，因为使用千兆以太网将带宽提高了5倍，并且Linux内核中TCP堆栈的定制将延迟减少了一半。LoBoSIII将拥有256个Pentium III 866MHz处理器，并为一半的计算机提供完全交换的Myrinet网络。LoBoS项目已经在美国国立卫生研究院生产了最强大的计算系统，用于大多数涉及计算化学工具的应用。它开辟了高性能计算的新领域，通过使用松耦合集群不断降低成本，同时提高可靠性。在集群上有效执行的应用程序类别已经被描述，并且正在努力更好地支持硬件中的延迟和带宽容忍算法。为PC集群环境开发新的生物信息学工具的主要工作是开发一种新的体系结构，用于集成不同的生物数据库和分配计算密集型任务。基因组学和蛋白质组学应用，如FASTA和BLAST，正被用于优化集群内的执行环境。集群非常适合大型数据库应用程序，因为每个计算节点都有自己的磁盘（最大限度地提高IO），并且可以将其工作负载配置为独立于其他节点（最大限度地提高效率）。

With the increased availability of parallel computer resources amenable to large scale scientific computing, it is essential to optimize the use of these resources. The efforts include the development of parallel computing techniques suitable for macromolecular simulation and the development of a parallel computer cluster and related software for high-efficiency simulations at low cost. Current projects include: - LoBoS: High performance computing using PC clusters - Development of parallel QM/MM methods - Development of bioinformatics tools for PC clusters - Development and evaluation of parallel algorithms for molecular dynamics - Development and support of parallel CHARMM - Development of Latency-tolerant algorithms for Parallel Computing The LoBoS (Lots of Boxes on Shelves), LoBoSII (and pending LoBoSIII/Biowulf II) supercomputers have been designed and constructed using commodity PCs. They provide a greater than 10-fold improvement in price/performance when compared with the traditional supercomputer vendor's offerings. The initial approach taken for LoBoS had been very successful for certain applications with 128 processors and multiple fast Ethernet connections per node. LoBoSII is a substantial improvement in scalability due to a 5-fold improvement in bandwidth using Gigabit Ethernet and customizations of the TCP stack in the Linux kernel have reduced latency by half. LoBoSIII will have 256 Pentium III 866MHz processors and a fully switched Myrinet network for half of the computers. The LoBoS Project has produced the most capable computational system at the NIH for most applications involving computational chemistry tools. It has opened up a new realm of high performance computing which continues to drive the cost down while improving reliability through the use of loosely-coupled clusters. The classes of applications that execute efficiently on clusters have been characterized and efforts to better support latency-and bandwidth-tolerant algorithms in hardware are underway. The main effort in developing new bioinformatics tools for the PC cluster environemnt is the development of a new architecture for the integration of disparate biological databases and for the distribution of compute-intensive tasks. Genomic and proteomic applications such as FASTA and BLAST are being used to optimize their execution environment within clusters by an order of magnitude. Clusters are uniquely suited to large database applications since each compute node has its own disk (maximizing IO) and its workload may be configured to be independent of other nodes (maximizing efficiency).