CC* Compute: BioBurst

CC* 计算：BioBurst

• 批准号: 1659104
• 负责人: Ronald Hawkins
• 金额: $ 49.41万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-02-01 至 2018-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1659104&HistoricalAwards=false
• 关键词: CC; Compute; BioBurst

The goal of the project is to deploy the BioBurst system to enhance the high performance computing capabilities at the University of California, San Diego, with technology designed to accelerate biological and life sciences research. The last few years have seen revolutionary advances in sequencing instruments for decoding genetic materials such as deoxyribonucleic acid (DNA) and ribonucleic acid (RNA). DNA and RNA carry the genetic code and control the production of proteins essential to life. A byproduct of this revolution in DNA/RNA sequencing technology is the production of vast amounts of data that must be stored and analyzed in order to achieve scientific progress. The manner of conducting these analysis stresses existing research computing systems in ways that must be overcome in order to expand the scope of investigations and reduce the time to results. The BioBurst system aims to augment the campus research computing system with innovative technology to speed up both data access and computation on DNA/RNA sequence data. A better understanding of DNA and RNA has the potential for advancing our Nation's health and well-being, enabling applications such as new insights into the biological mechanisms causing disease, and the development of new biofuels and agriculture products. The technical goal of the project is to implement a separately scheduled partition of the existing campus research computing system with technology designed to address important classes of bioinformatics computing including genomics, transcriptomics, and immune receptor repertoire analysis. The BioBurst system will incorporate the following major components: (1) I/O acceleration appliance with 40 terabytes of non-volatile memory and software designed to alleviate the small-block/small-file I/O problem characteristic of many bioinformatics codes; (2) An FPGA-based computational accelerator node that has been demonstrated to perform demultiplexing, read mapping, and variant calling of complete human genomes in 22 minutes; (3) 672 commodity computing cores which will access the I/O accelerator and provide a separately scheduled resource for running bioinformatics applications; (4) integration with a large scale parallel file system, which supports streaming I/O and has the capacity to stage large amounts of data associated with many bioinformatics studies; and 5) customization to the job scheduler to accommodate bioinformatics workflows, which can consist of hundreds to thousands of jobs submitted by a single user at one time. These components will be integrated as a partition of the existing production research computing system, providing a unique and highly usable resource by researchers across campus. A key objective is to provide bulk computing capacity to conduct in the order of 8,000 whole-genome analyses per year plus the ability for quick turnaround ( 60 min.) single-genome analyses, and sufficient solid state disk (SSD) capacity for staging associated working sets (200GB - 1TB).

该项目的目标是部署BioBurst系统，以提高加州大学圣地亚哥分校的高性能计算能力，其技术旨在加速生物和生命科学研究。 在过去的几年里，用于解码遗传物质（如脱氧核糖核酸（DNA）和核糖核酸（RNA））的测序仪器取得了革命性的进展。 DNA和RNA携带着遗传密码，控制着生命所必需的蛋白质的产生。 这场DNA/RNA测序技术革命的副产品是产生了大量必须存储和分析的数据，以实现科学进步。 进行这些分析的方式强调现有的研究计算系统的方式，必须克服，以扩大调查的范围，减少时间的结果。 BioBurst系统旨在通过创新技术增强校园研究计算系统，以加快DNA/RNA序列数据的数据访问和计算。 更好地了解DNA和RNA有可能促进我们国家的健康和福祉，使应用程序，如对导致疾病的生物机制的新见解，以及新的生物燃料和农产品的开发。 该项目的技术目标是对现有校园研究计算系统实施单独计划的分区，其技术旨在解决重要的生物信息学计算类别，包括基因组学、转录组学和免疫受体库分析。 BioBurst系统将包括以下主要组成部分：（1）I/O加速装置，具有40 TB的非易失性存储器和软件，旨在减轻许多生物信息学代码特有的小块/小文件I/O问题;（2）基于FPGA的计算加速器节点，已被证明可以在22分钟内完成完整人类基因组的解复用、读取映射和变异调用;（3）672个商用计算核心，它们将访问I/O加速器并为运行生物信息学应用程序提供单独调度的资源;（4）与大规模并行文件系统集成，该文件系统支持流式I/O并具有暂存与许多生物信息学研究相关的大量数据的能力;以及5）定制作业调度器以适应生物信息学工作流，其可以由单个用户一次提交的数百到数千个作业组成。 这些组件将被集成为现有生产研究计算系统的一个分区，为整个校园的研究人员提供独特且高度可用的资源。一个关键目标是提供大容量计算能力，每年进行8,000次全基因组分析，并具有快速周转（60分钟）的能力。单基因组分析，以及足够的固态磁盘（SSD）容量，用于暂存相关的工作集（200 GB-1 TB）。