MCCHE Precision Convergence Webinar Series with Dr. Amit Majumdar
Science Gateways – Enabling Seamless Large-Scale Modeling and Data Processing on Supercomputers for Domain Sciences with the Neuroscience Gateway as a Case Study
By Dr. Amit Majumdar
San Diego Supercomputer Center, University of California San Diego
With High-Level Panel of Leaders in Science, Technology, On-the-Ground Action, and Policy
This talk motivates the impact the science gateways are having on science and engineering research fields as they seamlessly enable large scale modeling, data processing and, more recently, AI/ML work on supercomputing resources. The talk will explain why and how science gateways are successful in eliminating and lowering administrative and technological barriers to using supercomputers by domain scientists for their computational work. It will discuss how science gateways are helping with education and training. The Neuroscience Gateway, which has been in operation since 2013, will be used as a case study to describe how it is enabling computational, cognitive and experimental neuroscientists with their research and relate to the US BRAIN Initiative which started in 2013, the European Human Brain Project which also started in 2013, and various such initiatives in brain research in various countries over the last decade.
About the speaker
Amit Majumdar is the Division Director of the Data Enabled Scientific Computing division at the San Diego Supercomputer Center and Associate Professor in the Department of Radiation Medicine and Applied Sciences at the University of California San Diego. One of his research interests has been to bring cyberinfrastructure to the biomedical research community to enable computational and data focused biomedical research. As a part of this he has collaborated with biomedical researchers such as neuroscientists and radiation oncologists and developed and supported science gateways. Two such science gateway projects are supporting the neuroscience community – the Neuroscience Gateway (NSG) project and the NeuroElectroMagnetic data Archive and tools Resource (NEMAR) project. His other research interests are in high performance computing (HPC), computational science, and cyberinfrastructure. He is PI/Co-PI on multiple research projects related to HPC and AI, neuroscience cyberinfrastructure, neuromorphic computing and education/outreach and which are funded by NSF, NIH, DOD and industry. He is the PI of the Voyager machine an AI-focused hardware-based supercomputer funded by NSF. He is the SDSC PI of the Intelligent Cyberinfrastructure with Computational Learning in the Environment (ICICLE) AI Institute funded by NSF. He is PI on multiple NIH grants where computing is involved in neuroscience research. He participates actively in training and outreach programs including mentoring students of diverse backgrounds. He is member of IEEE, SIAM, APS, Society for Neuroscience, and Organization for Computational Neuroscience.
About the series
The Precision Convergence series is launched to catalyze unique synergy between, on the one hand, novel partnerships across sciences, sectors and jurisdictions around targeted domains of real-world solutions, and on the other hand, a next generation convergence of AI with advanced research computing and other data and digital architectures such as PSC’s Bridges-2, and supporting data sharing frameworks such as HuBMAP, informing in a real time as possible the design, deployment and monitoring of solutions for adaptive real-world behaviour and context.
The Precision Convergence Webinar Series is co-hosted by The McGill Centre for the Convergence of Health and Economics (MCCHE) at McGill University and The Pittsburgh Supercomputing Center, a joint computational research centre between Carnegie Mellon University and the University of Pittsburgh.