课题基金 / 基金详情

MRI-R2: Acquisition of an Applied Computational Instrument

MRI-R2: Acquisition of an Applied Computational Instrument
MRI-R2:获取应用计算仪器
批准号:
0960354
负责人:
Allen Malony
金额:
$197.11万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-05-01 至 2013-09-30

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英文摘要
This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). Building on the success of a previousMRI-funded project, an interdisciplinary group of computer scientists, psychologists, biologists, chemists, and physicists at the University of Oregon is acquiring a large-scale computational resource, the Applied Computational Instrument for Scientific Synthesis (ACISS), to support continued cutting-edge scientific research in these areas. The ACISS hardware will consist of general purpose multicore computing nodes, high performance computing nodes augmented with GPGPU acceleration, a 400TB storage system, high-bandwidth networking infrastructure and additional computing resources that will be incorporated into an existing visualization lab in the Department of Computer and Information Science. A key part of the proposed infrastructure is the unique opportunity to manage ACISS as a computational science cloud. The ACISS infrastructure will allow an expanded the scope for the current projects in the areas of software tools for performance measurement, programming environments and languages for describing and executing complex simulations and scientific work flows, new algorithms for multiple sequence alignment and phylogenetic inference and undertake new projects in support of the domain sciences. Research projects that will benefit include: a) modeling neural networks in C. elegans to better understand the neural mechanisms responsible for chemotaxis and klinotaxis, and investigation of the evolution of genes involved in development and their role in speciation and phenotypic variation; b) development of neuroinformatic techniques used in brain imaging and analysis, integrating structural information from fMRI and other sources with EEG data; c) molecular modeling research, including the definition of new techniques for meso-scale modeling and applying computational methods to understand phase transitions and nitrogen fixation; d) astrophysical simulations of turbulent plasma flows that influence the early stages of planet formation. The ACISS infrastructure will provide the computational resources necessary for future multidisciplinary research. ACISS will establish a novel paradigm for computational science research and practice. The experience gained in early adoption of the ACISS cloud computing technologies will allow us to more rapidly apply this knowledge to create new scientific work flows, more productive research collaborations, and enhanced multidisciplinary education programs. Farther reaching, ACISS can be seen as a model for translational computational science, in which ACISS-based services function as cyber-incubators where new work flows for scientific research are prototyped.
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Ph.D. Forum at the International Conference on Parallel Processing (ICPP)
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    1833170
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    Standard Grant
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    $2.06万
  • 财政年份:
    2018
  • 负责人:
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SI2-SSI: Collaborative Research: A Glass Box Approach to Enabling Open, Deep Interactions in the HPC Toolchain
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SDCI HPC Improvement: High-Productivity Performance Engineering (Tools, Methods, Training) for NSF HPC Applications
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    2007
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ST-HEC: Collaborative Research: Scalable, Interoperable Tools to Support Autonomic Optimization of High-End Applications
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  • 资助金额:
    $23.01万
  • 财政年份:
    2004
  • 负责人:
    Allen Malony
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