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Collaborative Research: Community Infrastructure for General Relativistic MHD (CIGR)
PI:  Manuela Campanelli; Co-PI: (s): Joshua Faber, Hans-Peter Bischof, Carlos Lousto, Yosef Zlochower
Award:  NSF PHY-0903782 Dates:  10/01/2009—09/30/2012; Funds:  $300,000

Description

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.