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)提供资金的。广义相对论磁流体动力学(CIGR)协作社区基础设施将为广义相对论磁流体动力学(GRMHD)创建一个现代化、可扩展和开放的社区工具包和网络基础设施。这些工具将提高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，以加快模拟代码的开发，模拟代码能够准确地模拟重大挑战问题，如双中子星的合并、核心坍塌超新星和伽马射线爆发。CIGR包括四个核心推力，它们利用仙人掌框架积累的经验，可扩展的地毯自适应网格精化驱动器和由欧盟天体物理网络开发的广义相对论流体力学的Whisky代码：(I)为GRMHD提供一个功能丰富的工具包，研究小组可以使用和扩展它来建立自己的尖端生产代码；(Ii)为GRMHD提供开放的代码，将广义相对论流体力学、微观物理状态方程、磁流体动力学和辐射输运的组件整合在一起；(Iii)为数值相对论开发新的使能的网络基础设施，包括高度可靠和优化的输入/输出、分布式存储和档案、数据和模拟分类以及来源；以及(Iv)支持这些工具包和工具，用于日益增长的大型和复杂计算环境，如NSF的TeraGrid、能源部的LCF，并为即将到来的拍级和数据密集型环境做好准备，如NSF XD、Blue Waters和Datanet程序。

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.