- Research Activity
- Industry Gateway
- Education & Training
- ACI Leadership
- RDI2 ACI
The overarching goal of the Rutgers Discovery Informatics Institute (RDI2), New Jersey’s Center for Advanced Computation, is to establish a comprehensive and internationally competitive Computational and Data-Enabled Science and Engineering (CDS&E) effort at Rutgers University that can nurture the fundamental integration of research, education, and infrastructure. This integration will stimulate new thinking and new practices in CDS&E that will be catalyzed by cyberinfrastructure advances. Collectively, these efforts will address today’s grand challenges in science, engineering, and industry.
Recently, Professor Parashar served as program director in the Office of Cyberinfrastructure at the National Science Foundation (NSF), where he managed an approximately $150 million research portfolio. At NSF, he established and led the crosscutting Software Infrastructure for Sustained Innovation (SI2) program and the CI TraCS Computational Science Fellowship programs, was involved in establishing the Computing in the Cloud (CiC) program, and worked on the NSF-wide Cyberinfrastructure Framework for 21st Century Science and Engineering (CIF21) initiative.
Professor Parashar has held a visiting position at the eScience Institute at Edinburgh, UK (2009–2010); a joint research appointment with the Center for Subsurface Modeling at the University of Texas at Austin (1996–2006); and a visiting position at the Laboratoire d’InfoRmatique en Image et Systemes d’information (LIRIS), Lyon, France. He also has been a visiting fellow in the Department of Computing and Mathematical Sciences and DOE ASCI/ASAP Center at the California Institute of Technology (2000–2001), at the University of Chicago DOE ASCI/ASAP FLASH Center (1998), and at the Max-Planck Institute, Potsdam, Germany (1994–1998).
His research interests are in the broad area of parallel and distributed computing and include computational and data-enabled science and engineering; applied parallel and distributed computing (Cloud, Grid, HPC); extreme-scale computing; autonomic computing; data center provisioning and management; application-aware power/energy management; and pervasive computational ecosystems. A key focus of his current research is addressing the complexity of large-scale systems and applications through programming abstractions and systems.
Science and engineering research is becoming increasingly multidisciplinary. Therefore, a resource that can identify and cultivate effective collaborations and synergies is critical to success. To promote these synergies, RDI2 creates a research environment that bridges more traditional research boundaries and catalyzes socio-technical changes in research across all fields of science and engineering.
Key broad research thrusts include:
“Big data,” large-scale analytics, and computational modeling and simulations are playing an increasingly important role in industry. Businesses recognize the value of these activities and have made significant investments in both computational infrastructure and research and development activities. Industry partnerships in technology transfer, research, education, entrepreneurship, and economic development are integral aspects of RDI2. RDI2 will enable companies of all sizes and sectors to take advantage of advanced computing technology.
RDI2 will offer a variety of educational programs to Rutgers students, academic researchers, and industry researchers. These will include various certificate and degree programs, seminars that will be open to the public, and short training modules that will help academic and industry researchers acclimate to advanced computing hardware.
ACI is the core that permeates all aspects of RDI2 and includes facilities for high-performance computing and communications, data management, computational services, and advanced visualization. The goal is to support both science and engineering enabled by ACI, as well as the science and engineering required to develop and advance ACI. The Rutgers ACI should also provide global linkages to the national and international ACI that will be used, for example, to link observational instruments, data streams, experimental tools, and testbeds.
Key ACI resources provided by RDI2 include: