Rochester Institute of Technology

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Collaborative research: Frameworks: The Einstein Toolkit ecosystem: Enabling fundamental research in the era of multi-messenger astrophysics
PI: Yosef Zlochower; Co-PI: (s):Manuela Campanelli, Joshua Faber
Award:  NSF OAC-2004044 Dates: 07/01/2020—06/30/2024; Funds: $439,675


A team of experts from five institutions (University of Illinois Urbana-Champaign, Georgia Institute of Technology, Rochester Institute of Technology, Louisiana State University, and West Virginia University) are collaborating on further development of the Einstein Toolkit, a community-driven, open-source cyberinfrastructure ecosystem providing computational tools supporting research in computational astrophysics, gravitational physics, and fundamental science. The new tools address current and future challenges in gravitational wave source modeling, improve the scalability of the code base, and support an expanded science and user community around the Einstein Toolkit.

The Einstein Toolkit is a community-driven suite of research-grade Python codes for performing astrophysics and gravitational wave calculations. The code is open-source, accessible via Conda (an open source package management system) and represents a long-term investment by NSF in providing such computational infrastructure. The software is designed to simulate compact binary stars as sources of gravitational waves. This project focuses on the sustainability of the Einstein Toolkit; specific research efforts center around the development of three new software capabilities for the toolkit:

? CarpetX -- a new mesh refinement driver and interface between AMReX, a software framework containing the functionality to write massively parallel block-structured adaptive mesh refinement (AMR) code, and Cactus, a framework for building a variety of computing applications in science and engineering;

NRPy+ -- a user-friendly code generator based on Python; and

Canuda -- a new physics library to probe fundamental physics.

Integration of graphics processing units (GPUs) will incorporate modern heterogeneous computing devices into the system and will enhance the capability of the toolkit. The end product is sustainable through integration into the Einstein Toolkit, yet also includes an active community maintaining and enhancing the foundational components. Broader impacts are enhanced through training, documentation and a support infrastructure that reduces the barrier to adoption by the community. The team is also creating a science portal with additional educational and showcase resources.

This award by the Office of Advanced Cyberinfrastructure is jointly supported by the National Science Foundation's Big Idea activities in Windows on the Universe (WoU).

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.