Center for Scientific Computing and Visualization Research will acquire a new rapid prototyping machine
April 13, 2017
UMass Dartmouth Center for Scientific Computing and Visualization Research will acquire a new rapid prototyping machine, a powerful computer server intended for use in collaborative multidisciplinary research among faculty members and students from different departments with diverse programming background. The new rapid prototyping server (rps) is a single high-end Linux server with 3.2 GHz multicore Xeon CPUs, 256GB RAM, and can handle up to 4 GPUs. Popular rapid prototyping software such as anaconda python 2 and 3, Julia, MATLAB with parallel computing toolbox, and Mathematica with GPU support will also be installed. With convenient feature such as UMassD logon, the server can also be seen as an extension of faculty's office workstations or as a test machine prior to scaling up computing jobs to UMass Dartmouth multinode servers: ARNiE and HPCC or MGHPCC (UMass-wide supercomputer). The older rapid prototyping server will be repurposed as a machine for teaching introduction to scientific computing (MTH280), mathematical and computational consulting (MTH540), and high performance scientific computing (EAS520) courses. Prototyping projects currently conducted on the older machine includes but not limited to deep learning with Mathematica, numerical simulation of systems of PDEs, development of new time-stepping methods, and preconditioning techniques for generalized finite difference sparse systems. Smooth transition from older to new rps system will be expected in the summer of 2017.
The University of Massachusetts Dartmouth's Center for Scientific Computing & Visualization Research (CSCVR) has contributed 120 GPU servers to the UMass shared computational cluster installed at the MGHPCC (full article here)
The UMass shared cluster at the MGHPCC is a large (~15,000) processor-core supercomputer system that serves the entire UMass system's computational scientists. From astrophysicists at the Amherst and Dartmouth campuses, to biomedical researchers at Worcester, this key central facility provides the computational resources needed to advance world-class research programs across the system. While a large number of processors is the most common way to build powerful supercomputers today; lately advances in graphics processors (GPUs) has allowed them to be used as accelerators for scientific calculations often delivering a speed-up of over an order-of-magnitude.
UMass Dartmouth Graduate Student To Pursue the Rhythms of the Universe
March 30, 2017
Rahul Kashyap (EAS Ph.D. '17) has accepted an offer to work after graduation as a postdoctoral research scholar jointly at the Max Planck Institute for Gravitational Physics (also known as the Albert Einstein Institute) in Hanover, Germany, and the International Centre for Theoretical Sciences in Bengaluru, India. During his Ph.D. studies at UMass Dartmouth, Rahul investigated the nature of a class of exploding stars, or supernovae, using some of the largest supercomputers in the world. Rahul was supported on a Distinguished Doctoral Fellowship provided by the Graduate Studies Office, the Physics and Mathematics Department and the Center for Scientific Computing and Visualization Research. Please see the University's press release to learn more about Rahul's research.
Supercomputing-Enabled Advances in Science & Engineering
March 7, 2017
CSCVR Directors, Prof. Sigal Gottlieb and Prof. Gaurav Khanna are serving as guest editors for a special issue of the well-established IEEE / AIP journal Computing in Science & Engineering. The special issue is titled ”Supercomputing-Enabled Advances in Science & Engineering” and will publish papers that report on impactful advances enabled by large-scale computing in any area of science or engineering. All submitted papers will be peer-reviewed.