Computeserver Structural & Functional Image Analysis
计算服务器结构
基本信息
- 批准号:6730754
- 负责人:
- 金额:$ 49.6万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2004
- 资助国家:美国
- 起止时间:2004-04-01 至 2005-03-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
DESCRIPTION (provided by applicant):
This proposal requests funding for a Shared Instrument to support a new, state of the art, high performance computational cluster for structural and functional image analysis. Specifically, we are proposing a 344 node cluster, comprised of 2.8 Ghz Xenon processors, that will greatly enhance the ability of users of the Martinos Center to conduct their currently funded research projects. Four broad areas of users are identified, and will realize a dramatic benefit: a) fMRI studies (to increase the throughput of surface analysis and statistical characterization), b) voxel-based morphometry studies (to increase throughput on large morphometry studies), c) multimodal integration studies (to facilitate complex forward and inverse modeling used in EEGIMEG/MRI and diffuse optical tomography) and d) algorithm development users (to enhance turnaround on technique optimization, validation and implementation.) A common feature that makes this migration possible is the use of the Freesurfer processing stream. This software already has in place a comprehensive, demonstrated infrastructure for distributed processing. Each of these classes of users has operational solutions now that utilize an existing but out-dated multi-mode compute server. Each of these users, however, will benefit from a more advanced server and the increased capabilities it engenders.
The user community for this proposed instrument is broad; spanning 4 institutions (MGH, BWH, MIT, and BU) and many departments within these institutions. Also, this instrument enhances the performances capabilities of two Regional Resources, enabling these facilities to deliver greater computational power to their user.
描述(由申请人提供):
该提案要求提供一种共享工具的资金,以支持新的,最高的,高性能计算集群,用于结构和功能图像分析。具体来说,我们提出了一个由2.8 GHz氙处理器组成的344个节点群集,该群集将大大提高马提尼斯中心用户进行目前资助的研究项目的能力。确定了四个广泛的用户领域,并将实现巨大的好处:a)fMRI研究(增加表面分析和统计表征的吞吐量),b)基于体素的形态计量学研究(增加大型形态计量学研究的吞吐量),c)多模态整合研究(以促进复杂的和egemeg/diffors and tomime and tomime and tomime and tomime and tomime and tomime tontym and tomose(diffuse tonfime tonfime)(增强技术优化,验证和实现的周转。)使此迁移成为可能的常见功能是使用Freesurfer处理流。该软件已经建立了用于分布式处理的全面,展示的基础架构。这些类别的用户中的每一个都有运行解决方案,现在使用现有但过时的多模式计算服务器。但是,这些用户中的每一个都将受益于更高级的服务器及其产生的功能。
该提议的工具的用户社区很广泛;跨越4个机构(MGH,BWH,MIT和BU)以及这些机构中的许多部门。此外,该工具增强了两种区域资源的性能功能,使这些设施能够为用户提供更大的计算能力。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Bruce Fischl其他文献
Bruce Fischl的其他文献
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{{ truncateString('Bruce Fischl', 18)}}的其他基金
An acquisition and analysis pipeline for integrating MRI and neuropathology in TBI-related dementia and VCID
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- 资助金额:
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BRAIN CONNECTS: Mapping Connectivity of the Human Brainstem in a Nuclear Coordinate System
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Deep Learning for Detecting the Early Anatomical Effects of Alzheimer's Disease
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10658045 - 财政年份:2023
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$ 49.6万 - 项目类别:
Algorithms for cross-scale integration and analysis
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- 批准号:
10224850 - 财政年份:2020
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$ 49.6万 - 项目类别:
Algorithms for cross-scale integration and analysis
跨尺度集成和分析算法
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10038179 - 财政年份:2020
- 资助金额:
$ 49.6万 - 项目类别:
Segmenting Brain Structures for Neurological Disorders
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- 批准号:
10295766 - 财政年份:2018
- 资助金额:
$ 49.6万 - 项目类别:
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