MRI: Development of a Novel Computing Instrument for Big Data in Genomics
MRI: Development of a Novel Computing Instrument for Big Data in Genomics
批准号:
1337732
负责人:
Steven Lumetta
金额:
$180.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-09-15 至 2019-08-31
中文摘要
提案编号:13- 37732 PI:Lumetta,Steven S. 作者:Jongeneel,Cornelis维克托;罗宾逊,Gene E.; Sinha,Saurabh机构:伊利诺伊大学香槟分校职称: MRI/器械:面向大数据的新型计算仪器 项目建议:该项目开发CompGen,一种采用硬件-软件协同设计方法的仪器,旨在提供-生物学家和计算机科学家合作开发新算法的工具,这些算法在处理数据泛滥所必需的规模上显着更快,更准确; -支持各种数据分析和可视化的算法开发的软件框架和工具集; -开发加速器和映射到异构计算资源和分层数据库存储的框架。有前途的技术包括新兴的裸片堆叠和非易失性存储器技术以及加速器(GPU、FPGA、APU)。该项目汇集了遗传学家,生物信息学专家,计算机和算法设计师以及数据挖掘专家的多学科团队。将开展的研究包括对健康和社会问题有直接影响的广泛和折衷的各种问题。一些方向包括了解气候变化对基因表达和生态系统的影响,将遗传分析纳入医疗诊所,确定有效的抗生素,并探索低收入非洲裔美国母亲之间的压力,抑郁症和遗传学之间的社会基因组学关系。 CompGen提供了一个能够管理和处理基因组信息并开发新算法的环境。该仪器带来了颠覆性的计算架构和算法技术,以促进基因组数据的分析,同时提供高准确性的结果,对错误的恢复能力,以及随着数据量不断增长的可扩展性。它能够通过开发新的算法,模型和统计方法来解决基因组数据的规模和多样性的挑战。仪器开发的重点是减少数据量,优化存储层次结构,识别和实现的计算原语,数据可视化,数学工具包优化,性能和可靠性评估。这些发展预计将导致新的计算结构和硬件/软件架构,可以纳入分层数据库以及异构处理器的数据分析,压缩和优化。 更广泛的影响:除了服务于许多领域外,CompGen还将作为一种工具,用于教育学生和专业人员以有效的方式处理和分析基因组数据以及处理大数据。该仪器将服务于多学科课程,让学生获得实践研究经验,并为学生提供应用程序和工具的入门课程。将利用现有的外联和教育方案来宣传该文书。计划包括吸引数千名游客的开放日活动,Coursera课程和少数民族外联研讨会。一个名为Mytri的辅导工具将用于女学生之间的网络联系。此外,CompGen设计将通过从根本上改变基因组学研究中处理大数据集的方法而提供给其他人。为此,成立了一个由医院、公司和大学组成的研发联盟,以帮助确定需求,提供数据来源,充当早期采用者,并确保新技术顺利转移到广泛使用。
英文摘要
Proposal #: 13-37732PI(s): Lumetta, Steven S. Iyer, Ravishankar; Jongeneel, Cornelis Victor; Robinson, Gene E.; Sinha, SaurabhInstitution: University of Illinois - Urbana-ChampaignTitle: MRI/Dev.: Novel Computing Instrument for Big Data Project Proposed:This project, developing CompGen, an instrument that adopts a hardware-software co-design approach, aims to provide a- Vehicle for biologists and computer scientists to collaborate and develop new algorithms that are significantly faster and more accurate at a scale essential for handling the data deluge; - Software framework and tool set for algorithm development that support diverse data analysis and visualization; - Framework for developing accelerators and mapping to heterogeneous computational resources and hierarchical database storage. Promising technologies include emerging die-stacked and non-volatile memory technologies as well as accelerators (GPUs, FPGAs, APUs). The project brings together a multidisciplinary team of geneticists, bioinformatics specialists, computer and algorithms designers, and data mining experts. The research to be enabled includes a wide and eclectic variety of problems with direct impact on health and social issues. Some directions include understanding the impact of climate change on gene expression and ecosystems, bringing genetic analysis into medical clinics, identifying effective antibiotics, and exploring socio-genomics relations between stress, depression, and genetics among low-income African-American mothers. CompGen provides an environment that enables managing and processing genomic information and developing new algorithms. The instrument brings disruptive computing architectures and algorithmic techniques to facilitate analysis of genomic data while providing high accuracy results, resilience to errors, and scalability with growing volumes of data. It enables addressing the challenges of scale and diversity in genomic data through the development of new algorithms, models, and statistical methods. The instrument development focuses on reduction of data volume, optimization of storage hierarchy, identification and implementation of computational primitives, data visualization, mathematical toolkit optimization, and performance and reliability assessment. These developments are expected to lead to new computational structures and hardware/software architectures that can be incorporated into hierarchical databases as well as heterogeneous processors for data analysis, compression, and optimization. Broader Impacts: In addition to serving many areas, CompGen will serve as a tool for educating students and professionals in efficient ways to process and analyze genomic data and for handling big data in general. The instrument will serve multidisciplinary classes in which students gain hands-on research experience and introductory classes that expose students to applications and tools. Existing outreach and education programs will be utilized to expose the instrument. Plans include Open House events attracting thousands of visitors, Coursera courses, and minority outreach workshops. A mentoring tool, Mytri, will be used for networking among female students. Moreover, the CompGen design will be made available to others by fundamentally changing the methods by which big datasets are handled in genomics research. To this effect, an R&D consortium of hospitals, companies, and universities has been established to help identify needs, provide sources of data, act as early adopters, and ensure that new technologies are transferred smoothly into widespread use.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
DOI:
10.1145/3445814.3446739
发表时间:
2021-02
期刊:
Proceedings of the 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems
影响因子:
--
作者:
[Subho Sankar Banerjee;Saurabh Jha;Z. Kalbarczyk;R. Iyer]
通讯作者:
Subho Sankar Banerjee;Saurabh Jha;Z. Kalbarczyk;R. Iyer
CAREER: An Adaptive, High-Performance Software Infrastructure for Hierarchical Systems
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批准号:9984492
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项目类别:Continuing Grant
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资助金额:$25.96万
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财政年份:2000
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负责人:Steven Lumetta
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依托单位:
国内基金
海外基金
水稻边界发育缺陷突变体abnormal boundary development(abd)的基因克隆与功能分析
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批准号:32070202
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项目类别:面上项目
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资助金额:58.0万元
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批准年份:2020
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负责人:汪泉
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依托单位:
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
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项目类别:--
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资助金额:40万元
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批准年份:2020
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负责人:Vikrant Gupta
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依托单位: