A High Performance Server for Data-Intensive Computation

描述(由申请人提供)：麻省理工学院计算和系统生物学倡议(CSBi)申请资金购买具有存储区域网络数据存储(SMP-SAN)的对称多处理服务器，使科学家能够处理与各种系统生物学项目相关的数据密集型计算问题。这种集中访问的计算资源对于从事生物学研究基本方面的几个实验室的即时进展至关重要。在本提案中，我们描述了一个重要且不断增长的计算生物学问题子集，这些问题由于数据量大而无法使用连接到网络连接存储(NAS)设备上的数据的传统32位集群来解决。我们打算通过SMP服务器的基本配置来增加CSBi高性能计算(HPC)核心和怀特黑德-麻省理工学院生物成像中心的可用计算资源，SMP服务器包含16个位Itanium2处理器，具有GB内存，运行通用的位Linux操作系统(OS)，以及具有多个光纤通道连接的数TB数据存储，从而实现每秒数千兆位的低延迟带宽。SMP-SAN将允许研究人员轻松收集数百GB到TB的数据，并直接解决该提案中描述的两个主要生物学领域的计算需求：成像和蛋白质组学。这些项目的范围从研究细胞行为的成像技术和癌症诊断的非侵入性方法到识别、理解和模拟蛋白质以帮助药物发现和临床诊断。该资源将位于怀特黑德-麻省理工学院生物成像中心，并与CSBi HPC资源整合。Biolmaging中心和CSBi HPC Core在高性能计算系统和大型数据存储系统的管理方面拥有丰富的经验，并致力于对拟议系统的支持和维护。

DESCRIPTION (provided by applicant): The Computational and Systems Biology Initiative at MIT (CSBi) requests funds to purchase a symmetric multi-processing server with storage area network data storage (SMP-SAN) enabling scientists to handle data-intensive computational problems related to a wide variety of Systems Biology projects. This centrally- accessible computational resource is critically required for the immediate progress of several labs engaged in fundamental aspects of biological research. In this proposal, we describe a significant and growing subset of computational biology problems that due to large data sizes cannot be tackled using traditional 32-bit clusters connected to data on network attached storage (NAS) devices. It is our intention to augment the computational resources available in the CSBi High-Performance Computing (HPC) core and the Whitehead-MIT Biolmaging Center with a base configuration of an SMP server containing sixteen 64-bit Itanium2 processors with 64 gigabytes (GB) memory, running a generic 64-bit capable linux operating system (OS), and several terabytes (TBs) of data storage with multiple fiber-channel connections enabling multi-gigabit per second low latency bandwidth. The SMP-SAN will allow researchers to easily collect hundreds of GB to TB of data and directly address the computational needs in two major areas of biology described in this proposal: imaging and proteomics. The projects range from development of imaging technologies to study cellular behavior and non-invasive methods for cancer diagnosis to identifying, understanding and modeling proteins to help in drug discovery and clinical diagnosis. The resource will be located in the Whitehead-MIT Biolmaging Center and integrated with the CSBi HPC resources. The Biolmaging Center and the CSBi HPC Core have extensive experience with management of high-performance computing systems and large data storage systems and are committed to the support and maintenance of the proposed system.