MRI: Acquistion of A Scalable Instrument for Discovery through Computing

提案编号：CNS 08- 21527 PI：Raghavan，Padma Chen，Long-Quing;哈德逊，Peter J.; Kandemir，Mahmut T.;机构：宾夕法尼亚州立大学 大学公园，宾夕法尼亚州16802- 700标题： MRI/采集：通过计算发现的可扩展仪器的获得MRI通过计算发现的可扩展仪器的获得这个来自主要研究仪器计划（MRI）的奖项为宾夕法尼亚州立大学购买万亿级先进计算仪器提供资金。 该仪器使来自七个学科（生物，材料和社会科学，计算机和信息科学，工程，教育和地球科学）的研究人员能够通过计算进行虚拟实验，以发现和设计。 研究项目涉及：传染病动力学的预测网络建模，设计新的压电材料，设计下一代芯片多处理器，模拟人类互动以促进虚拟社区的学习，以及关键区域环境观测站的发展。 尽管这些项目各不相同，但它们都面临着计算可扩展性方面的挑战，需要解决这些挑战才能实现科学进步，而科学进步往往依赖于解决代表足够详细和复杂程度的大型问题。该仪器将成为多学科协作环境的核心，以实现变革性方法来解决多层次扩展的挑战。它将支持一系列综合研究，教育，培训和推广活动，以：（i）通过将扩展方法从一个领域转移到另一个领域，实现跨项目的协作扩展，同时解决单个项目中的算法，系统或仪器扩展挑战，（ii）通过工业伙伴关系促进技术转移，以及（iii）增长和增强有限的计算科学人才库的多样性。

Proposal #: CNS 08-21527PI(s): Raghavan, Padma Chen, Long-Quing; Hudson, Peter J.; Kandemir, Mahmut T.; Smith, Brian K.Institution: Pennsylvania State University University Park, PA 16802-700Title: MRI/Acq.: Acq.of A Scalable Instrument for Discovery through ComputingMRI Acquisition of a Scalable Instrument for Discovery through ComputingThis award from the Major Research Instrumentation Program (MRI)provides funds for the acquisition of a terascale advanced computinginstrument at the Pennsylvania State University. The instrumentwill enable researchers from seven disciplines (biological, materialsand social sciences, computer and information science, engineering,education, and geosciences), to perform virtual experiments towarddiscovery and design through computing. Research projects concern:predictive network modeling of infectious disease dynamics, designingnew piezoelectric materials, designing next-generation chipmultiprocessors, modeling human interactions to promote learningin virtual communities, and the development of a critical zoneenvironmental observatory. Despite their diversity, these projectsshare computational scalability challenges to be addressed forenabling scientific advances that often depend on solving largeproblems representing a sufficient level of detail and complexity.The instrument will form the core of a multidisciplinary collaborativeenvironment to enable transformative approaches to address thechallenges of scaling at multiple levels. It will support a set ofintegrated research, education, training, and outreach activitiesto: (i) enable collaborative scaling across projects through thetransfer of scaling approaches from one domain into another, whileaddressing algorithmic, system, or instrument scaling challengeswithin individual projects, (ii) promote technology-transfer throughindustrial partnerships, and (iii) grow and enhance the diversityof the limited computational science talent pool.