ITR - ASE - [int+dmc]: Storage Based Supercomputing for Scientific Applications

ITR - ASE - [int dmc]：用于科学应用的基于存储的超级计算

• 批准号: 0427794
• 负责人: Mark Franklin
• 金额: --
• 依托单位: Washington University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-15 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0427794&HistoricalAwards=false
• 关键词: ITR; ASE; int+dmc; Storage; Based

ITR - ASE - [int+dmc]: Storage Based Supercomputing for Scientific ApplicationsAbstractIn many scientific computing applications the size of the data sets, already in the range of multiple terabytes, continues to grow rapidly. The time required to move this data from magnetic media, across a system bus into main memory, and then execute code to perform a computation is prohibitive. We are addressing the bottleneck by moving the computations to be implemented close to the magnetic media in fast, customizable hardware tailored to the application. We will explore the benefits associated with our proposed architecture on two specific application domains: genomics and astrophysics. In the genomics domain we will explore new approaches to discovering similarities between biological sequences. In the astrophysics domain we will examine the processing of gamma ray burst data.The results of this research will directly translate into more capability in scientific computations that are dependent upon large data sets. This will have a direct positive impact on the fields of astrophysics and genomics. The impact, however, will go well beyond these domains since the tools, techniques and architecture developed will be applicable to a wide range of scientific computing problems. We are developing a computing system that allows effective exploration of the huge and growing datasets that are central to modern scientific discovery. This new computer architecture is a central and critical instrument, analogous to the telescope and microscope, in moving forward scientific boundaries.

ITR-ASE- [int+dmc]：科学应用中基于存储的超级计算摘要在许多科学计算应用中，数据集的大小已经在几个TB的范围内，继续快速增长。 将这些数据从磁介质通过系统总线移动到主存储器中，然后执行代码以执行计算所需的时间是令人望而却步的。 我们正在解决这个瓶颈，将计算移动到接近磁介质的位置，并为应用程序量身定制快速、可定制的硬件。 我们将探讨与我们提出的架构在两个特定的应用领域：基因组学和天体物理学的好处。在基因组学领域，我们将探索新的方法来发现生物序列之间的相似性。在天体物理学领域，我们将研究伽马射线暴数据的处理。这项研究的结果将直接转化为依赖于大数据集的科学计算的更多能力。 这将对天体物理学和基因组学领域产生直接的积极影响。然而，影响将远远超出这些领域，因为开发的工具，技术和架构将适用于广泛的科学计算问题。 我们正在开发一种计算系统，可以有效探索对现代科学发现至关重要的庞大且不断增长的数据集。 这种新的计算机体系结构是一种核心和关键的工具，类似于望远镜和显微镜，在推进科学边界方面。