To bring cosmological simulations into the petascale era, we are collaborating with University of Chicago and Princeton University on the development of PetaART. The Adaptive Refinement Tree (ART) code, a oct-based AMR simuation package, uses a combination of multi-level particle-mesh and shock-capturing Eulerian methods for simulating the evolution of dark matter and gas, respectively. It was originally developed by A. Kravtsov (UofC) in collaboration iwth A. Klypin and A. Khokhlov, with N. Gnedin and D. Rudd joining the team in 2003.
Our goals are: (1) to achieve petascale level performance for the ART cosmological code by improving load balancing, communication performance, and the hybrid parallelization mode on multi-core/multi-processor nodes on petascale platforms; (2) to develop a robust fault-tolerance mechanism for petascale ART simulations; (3) to provide a user-level interface and documentation for public release of ART under an open source license; and (4) to produce state-of-the-art cosmological simulations that will result in a rich scientific output and a valuable repository of simulation results for the astrophysical community. The petascale cosmological simulations resulting from this work will lead to major breakthroughs in our understanding of galaxy formation and will provide critical theoretical support for forthcoming large observational surveys designed to probe the matter and energy content of our universe and constrain properties of the mysterious dark matter and dark energy.
Members:This work is supported by US National Science Foundation.