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The Center for Scientific Computing and Data Science Research at the University of Massachusetts Dartmouth focuses on computationally-driven research that addresses the pressing needs of modern engineering, mechanics, fluid dynamics, and electromagnetics. Our annual HPC Day event showcases on-going scientific research in Massachusetts that is enabled through high-performance computing.

The research groups at the Center span a wide range of the applied sciences departments at UMassD, including

CSCDR member's work featured in Nature

CSCDR member Collin Capano had his work recently featured in Nature. The article discusses a major discovery in astrophysics by observing new features in blackhole ringing. Researchers, including Collin Capano, analyzed data from the LIGO and Virgo detectors, finding evidence of novel vibrations produced by a newly formed black hole as it settled into a spherical shape. This black hole, created by the largest merger ever detected, challenges some accepted theories due to its massive size, equivalent to 150 times the mass of the Sun. This discovery marks the first time such post-merger vibrations, a long-theorized phenomenon, have been observed. For more details, you can read the full article on Nature's website.

Center for Scientific Computing and Data Science Research Inaugurates New Computer Cluster funded by AFOSR DURIP award

The Center for Scientific Computing and Data Science Research (CSCDR) completed the purchase and installation of a new computer cluster, which was installed as part of the UNITY collaboration. This cluster was funded by a $600K award from the Air Force Office of Scientific Research (AFOSR) Defense University Research Instrumentation Program (DURIP), and will foster the development and testing of novel mathematical methods suitable for large-scale parallel scientific computing and data science applications. This is the fourth equipment grant award the CSCDR has secured, resulting in the purchase of over $1.6M in shared research computing hardware.

The proposal was developed by a team of computational scientists affiliated with the CSCDR: Alireza Asadpoure, Collin Capano, Yanlai Chen, Zheng Chen, Geoffrey W. Cowles, Scott Field, Sigal Gottlieb, Alfa Heryudono, Gaurav Khanna, Arghavan Louhghalam, Maricris Mayes, Mehdi Raessi, and Mazdak Tootkaboni. The projects that will be enabled by the new cluster focus on the development of innovative computational mathematics and data science algorithms that are of interest to the AFOSR, including the development of novel and efficient algorithms; mathematical methods for model complexity reduction; data analytics approaches including machine learning and similar approaches; development of novel materials including metamaterials, multi-phase architected materials, quantum materials, and materials for energy storage.

The new cluster consists of 53 compute nodes, each with 64 Intel x86 cores connected by a high speed, low latency Infiniband network, 3 energy efficient nodes, each with an 80-core ARM architecture processor, and 1 GPU node with 4x NVIDIA A100 GPUs on an NVLINK interconnect. The installed hardware comprises a total of 3,696 compute cores, 4 GPUs, and 15TB of memory and has an aggregate theoretical capability of completing 300 trillion double-precision calculations each second (Tflops FP64). The cluster was designed and built by Microway Inc., Plymouth MA.

The hardware has been integrated into the UNITY Machine at the Mass Green High Performance Computing Center in Holyoke, MA. UNITY represents a partnership of UMass Dartmouth, UMass Amherst, and the University of Rhode Island and offers researchers over 12,000 cores and 1000 GPUs as well as IT and facilitator support. UMassD faculty all have access to the entire Unity cluster.

CSCDR faculty and students featured in Quanta for their groundbreaking work on understanding Type Ia supernovas

Numerical simulations carried out by Professor Robert Fisher (Physics) and his research group Niranjan Roy, Vishal Tiwari, Daniel Kosakowski, and Dr. Rahul Kashyap have led to a new understanding of the role binary white dwarf systems play in understanding Type Ia supernovas. The results featured were published in an Astrophysical Journal Letter earlier this year. The full Quanta article can be found here