Award Abstract # 1458495
Bilateral BBSRC-NSF/BIO: Collaborative Research: ABI Development: Seamless Integration of Neuroscience Models and Tools with HPC - Easy Path to Supercomputing for Neuroscience

NSF Org: DBI
Division of Biological Infrastructure
Recipient: YALE UNIV
Initial Amendment Date: July 23, 2015
Latest Amendment Date: September 14, 2015
Award Number: 1458495
Award Instrument: Standard Grant
Program Manager: Peter McCartney
DBI
 Division of Biological Infrastructure
BIO
 Directorate for Biological Sciences
Start Date: August 1, 2015
End Date: November 30, 2018 (Estimated)
Total Intended Award Amount: $129,624.00
Total Awarded Amount to Date: $129,624.00
Funds Obligated to Date: FY 2015 = $129,624.00
History of Investigator:
  • Nicholas Carnevale (Principal Investigator)
    ted.carnevale@yale.edu
Recipient Sponsored Research Office: Yale University
150 MUNSON ST
NEW HAVEN
CT  US  06511-3572
(203)785-4689
Sponsor Congressional District: 03
Primary Place of Performance: Yale School of Medicine
330 Cedar St.
New Haven
CT  US  06510-3218
Primary Place of Performance
Congressional District:
03
Unique Entity Identifier (UEI): FL6GV84CKN57
Parent UEI: FL6GV84CKN57
NSF Program(s): ADVANCES IN BIO INFORMATICS,
CYBERINFRASTRUCTURE,
Cross-BIO Activities
Primary Program Source: 01001516DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 8089, 8091
Program Element Code(s): 116500, 723100, 727500
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.074

ABSTRACT

This project is a collaboration between the University of California San Diego and Yale University to develop a science gateway for the computational neuroscience community. A gateway such as this helps improve our understanding of how the brain works by making it easier for neuroscientists to use complex digital models of brain cells and circuits in their research. Powerful software has been developed for building and using models, and on-line resources such as Open Source Brain (OSB), ModelDB, Neuroscience Information Framework (NIF), and OpenWorm have been created to help neuroscientists find existing models, collaborate in developing new ones, and share the results of their work with others. However, models are becoming too complex for the computer hardware that is available to most neuroscientists, resulting in a critical need to use high performance computing resources (HPC). This work extends an existing Neuroscience Gateway (NSG), which was developed with support from NSF to eliminate or reduce many of the technical and administrative difficulties that previously limited neuroscientists' access to HPC (http://www.nsgportal.org/). That said, NSG users must still log in, upload models, launch simulations, and download results--a process that involves many time-consuming, error-prone steps. The expanded NSG-R will eliminate these steps by enabling on-demand, automated communication between itself and familiar working environments including resources like OSB and others mentioned above, and even with neural simulation software running on neuroscientists' own laptop and desktop computers.

This seamless access to HPC is implemented in NSG-R by a software infrastructure that uses REpresentational State Transfer ("REST", the R in NSG-R). NSG-R utilizes set of web services which expose the capabilities of NSG for access via publicly available application programmer interfaces. This will allow users of neuroscience resources such as OSB, ModelDB, NIF and OpenWorm to readily access HPC from their respective websites via NSG-R. This enhances the usefulness of NSG-R, other neuroscience resources like OSB, and widely used neural simulators such as NEURON, GENESIS, PyNN, NEST, Brian and MOOSE. It also results in greater research productivity and enables wider use of large scale computational modeling by scientists and students. NSG-R will accelerate progress in brain science, and have far-reaching beneficial effects on related fields such as robotics and engineering of adaptive and learning systems. It will widen opportunities for educational and career advancement in neuroscience and engineering. Furthermore, by removing barriers that traditionally have limited access to HPC, NSG-R levels the playing field for all students and researchers regardless of their institutional affiliation. NSG-R, a free and open neuroscience gateway infrastructure, will naturally be a ready entry point for students and researchers from historically underrepresented schools and colleges. NSG-R workshops will be hosted at minority serving institutions (MSI) and opportunities for students to do internships with the NSG-R team at the University of California San Diego will be provided.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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A. Majumdar, S. Sivagnanam, K. Yoshimoto, T. Carnevale ""Understanding the Evolving Cyberinfrastructure Needs of the Neuroscience Community"" Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale (XSEDE16). ACM, New York, NY, USA, , Article 45 , 7 pages. , 2016 DOI: http://dx.doi.org/10.1
Majumdar A, Sivagnanam S, Carnevale NT, Yoshimoto K, Gleeson P, Quintana A and Silver RA ""Neuroscience Gateway - Cyberinfrastructure Providing Supercomputing Resources for Large Scale Computational Neuroscience Research"" Front. Neuroinform. Conference Abstract: Neuroinformatics 2016. Neuroinformatics 2016, Reading, United Kingdom, 3 Sep - 4 , 2016 doi: 10.3389/conf.fninf.2016.20.00008
P. S. Kumbhar, S. Sivagnanam, K. Yoshimoto, M. Hines, T. Carnevale and A. Majumdar. ""Performance Analysis of Computational Neuroscience Software NEURON on Knights Corner Many Core Processors"" Software Challenges to Exascale Computing, Dec 13-14, 2018, Delhi, India, Springer Communications in Computer and Information Science (CCIS). , 2018
S. Sivagnanam, K. Yoshimoto, T. Carnevale, A. Majumdar ""The Neuroscience Gateway - Enabling Large Scale Modeling and Data Processing in Neuroscience"" Practice & Experience in Advanced Research Computing PEARC18, Pittsburgh, PA, July 22-26 , 2018

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

The NSG project began in 2012 with support from the NSF. Its initial goal was to catalyze progress in computational neuroscience by reducing technical and administrative barriers that neuroscientists faced in large scale modeling projects involving tools and software which require and run efficiently on high performance computing (HPC) resources. The NSG project was followed in 2015 by the NSG-R project, which added a programmatic interface to NSG so that neuroscientists could more easily automate the process of setting up and controlling modeling projects. NSG's success is reflected in the facts that (1) its base of registered users has grown continually since it started operation in early 2013 (more than 800 at present), (2) every year the NSG team successfully acquires ever larger allocations of supercomputer time (recently more than 10,000,000 core hours/year) on academic HPC resources of the Extreme Science and Engineering Discovery (XSEDE - that coordinates NSF supercomputer centers) program by writing proposals that go through an extremely competitive peer review process, and (3) it has contributed to large number of publications and Ph.D. thesis. At this time, we know of more than 100 reports of research that has been enabled by NSG. In recent years experimentalists, cognitive neuroscientists and others have begun using NSG for brain image data processing, data analysis and machine learning. NSG now provides over 20 tools on HPC resources for modeling, simulation and data processing.


Last Modified: 02/28/2019
Modified by: Nicholas T Carnevale

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