MRI: Acquistion of A Scalable Instrument for Discovery through Computing

提议#：CNS 08-21527PI(S)：Raghavan，Padma Chen，Long-Quing；Hudson，Peter J.；Kandemir，Mahmut T.；Smith，Brian K.机构：宾夕法尼亚州立大学园区，PA 16802-700标题：MRI/Acq.：获得通过计算发现的可扩展仪器MRI收购通过计算发现的可扩展仪器该奖项由主要研究仪器计划提供资金，用于在宾夕法尼亚州立大学购买兆级高级计算仪器。该仪器将使来自七个学科(生物、材料和社会科学、计算机和信息科学、工程学、教育和地球科学)的研究人员能够通过计算进行虚拟实验和发现和设计。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，为人类互动建模以促进在虚拟社区中的学习，以及开发关键区域环境观测站。尽管这些项目多种多样，但在推动科学进步方面，这些项目都面临着共同的计算可伸缩性挑战，而科学进步往往取决于解决代表足够详细和复杂程度的大问题。该工具将形成多学科协作环境的核心，以实现变革性的方法，以解决在多个水平上进行缩放的挑战。它将支持一套综合的研究、教育、培训和外联活动：(I)通过将缩放方法从一个领域转移到另一个领域，实现跨项目的协作缩放，同时解决单个项目中的算法、系统或仪器的缩放挑战，(Ii)通过产业伙伴关系促进技术转让，以及(Iii)扩大和加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.