Collaborative Research: Community Infrastructure for General Relativistic MHD (CIGR)

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。广义相对论磁流体动力学社区基础设施（CIGR）合作将为广义相对论磁流体动力学（GRMHD）创建一个现代的、可扩展的、开放的社区工具包和网络基础设施。这些工具将推进数值相对论和计算天体物理学领域的计算能力，并提供所需的协作基础设施，以加速能够精确模拟重大挑战问题的模拟代码的开发，如双中子星合并、核心坍缩超新星和伽马射线暴。CIGR包括四个核心推力，利用Cactus框架、可扩展的Carpet自适应网格细化驱动程序和由欧盟天体物理网络开发的用于广义相对论流体力学的Whisky代码积累的经验：(i)为GRMHD提供一个功能强大的工具包，研究小组可以使用和扩展该工具包来构建自己的尖端生产代码；（ii）提供GRMHD的开放代码，将广义相对论流体力学、微物理状态方程、磁流体力学和辐射输运的组件集成在一起；（iii）为数值相对论开发新的网络基础设施，包括高度可靠和优化的输入/输出、分布式存储和存档、数据和模拟分类和来源；（iv）支持这些工具包和工具，以增加大型和复杂的计算环境，如NSF的TeraGrid， DOE的LCF，并为即将到来的千兆级和数据密集型环境，如NSF XD， Blue Waters和DataNet计划做好准备。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). The Community Infrastructure for General Relativistic Magnetohydrodynamics (CIGR) collaboration will create a modern, scalable, and open, community toolkit and cyberinfrastructure for general relativistic magnetohydrodynamics (GRMHD). These tools will advance computational capabilities across the fields of numerical relativity and computational astrophysics and provide the collaborative infrastructure needed to accelerate the development of simulation codes able to accurately model grand challenge problems such as the coalescence of binary neutron stars, core-collapse supernovae, and gamma-ray bursts.CIGR includes four core thrusts that capitalize on accumulated experience with the Cactus framework, the scalable Carpet adaptive mesh refinement driver and the Whisky code for general relativistic hydrodynamics developed by the European Union Astrophysics Network: (i) providing a featureful toolkit for GRMHD that research groups can use and extend to build their own cutting edge production codes; (ii) providing an open code for GRMHD that integrates together components for general relativistic hydrodynamics, microphysical equations of state, magnetohydrodynamics, and radiation transport; (iii) developing new enabling cyberinfrastructure for numerical relativity, including highly reliable and optimized input/output, distributed storage and archives, data and simulation classification and provenance; and (iv) supporting these toolkits and tools on increasing large and complex computing environments such as the NSF's TeraGrid, DOE's LCF, and prepare for soon to arrive petascale and data-intensive environments such as NSF XD, Blue Waters and DataNet programs.