MRI: Development of a Novel Computing Instrument for Big Data in Genomics

提案#：13-37732PI(S)：Lumetta，Steven S.Iyer，Ravishankar；Jongenel，Cornelis Victor；Robinson，gene E.；Sinha，Saurabh研究所：伊利诺伊大学厄巴纳香槟分校标题：磁共振/开发：大数据项目的新型计算工具建议：这个项目，开发CompGen，一个采用硬件-软件协同设计方法的工具，旨在为生物学家和计算机科学家提供一种工具，以合作和开发新的算法，这些算法在处理数据泛滥的关键规模上显著更快和更准确；-用于算法开发的软件框架和工具集，支持不同的数据分析和可视化；-用于开发加速器和映射到不同计算资源和分层数据库存储的框架。前景看好的技术包括新兴的芯片堆叠和非易失性存储器技术以及加速器(GPU、FPGA、APU)。该项目汇集了一个由遗传学家、生物信息学专家、计算机和算法设计师以及数据挖掘专家组成的多学科团队。将能够进行的研究包括各种直接影响健康和社会问题的广泛和折衷的问题。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，将基因分析引入医疗诊所，确定有效的抗生素，以及探索低收入非裔美国母亲的压力、抑郁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以及开发新算法的环境。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，同时提供高精度的结果、对错误的恢复能力和随着数据量的增长而进行的可扩展性。它能够通过开发新的算法、模型和统计方法来应对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，识别和实现计算原语，数据可视化，数学工具包优化，以及性能和可靠性评估。预计这些发展将导致新的计算结构和硬件/软件体系结构，这些结构和硬件/软件体系结构可以合并到分层数据库以及用于数据分析、压缩和优化的异类处理器中。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，教育学生和专业人员以高效的方式处理和分析基因组数据，并总体上处理大数据。该仪器将为多学科课程提供服务，在这些课程中，学生将获得实践研究经验，以及让学生接触应用程序和工具的入门课程。将利用现有的外展和教育计划来揭露这一工具。计划包括吸引数千名参观者的开放参观活动、Coursera课程和少数族裔外联讲习班。一种名为Mytri的辅导工具将用于在女学生之间建立网络联系。此外，CompGen的设计将通过从根本上改变基因组研究中处理大数据集的方法而为其他人所用。为此，已经建立了一个由医院、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化为广泛使用。

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.