Development of Advanced Computer Hardware and Software

随着适合大规模科学计算的并行计算机资源的可用性的增加，优化这些资源的使用是至关重要的。 这些努力包括开发适用于大分子模拟的并行计算技术，以及开发并行计算机集群和相关软件，以低成本进行高效率模拟。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 - 开发和支持并行CHARMM -开发用于并行计算的延迟容忍算法LoBoS（货架上的大量盒子），LoBoSII（和待定的LoBoSIII/Biowulf II）超级计算机已经使用商品PC设计和构建。 与传统的超级计算机供应商的产品相比，它们在性价比方面提供了10倍以上的改进。LoBoS最初采用的方法在某些应用中非常成功，每个节点有128个处理器和多个快速以太网连接。 LoBoSII在可扩展性方面有了实质性的改进，因为使用千兆以太网的带宽提高了5倍，并且Linux内核中的TCP堆栈定制将延迟减少了一半。 LoBoSIII将有256个奔腾III 866 MHz处理器和一个完全交换的Myrinet网络，用于一半的计算机。LoBoS项目已经为涉及计算化学工具的大多数应用程序在NIH产生了最强大的计算系统。 它开辟了高性能计算的新领域，通过使用松散耦合的集群，在提高可靠性的同时继续降低成本。 在集群上高效执行的应用程序的类别已经得到了表征，并且正在努力在硬件中更好地支持延迟和带宽容忍算法。在开发新的生物信息学工具的PC集群集群的主要努力是开发一个新的体系结构的整合不同的生物数据库和计算密集型任务的分布。 基因组学和蛋白质组学应用程序，如FASTA和BLAST，正在被用来优化集群内的执行环境的数量级。 集群特别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（最大化IO），并且其工作负载可以配置为独立于其他节点（最大化效率）。

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).