Jetstream: A self-provisoned, scalable science and engineering cloud environment

The paper describes the motivation behind Jetstream, its functions, hardware configuration, software environment, user interface, design, use cases, relationships with other projects such as Wrangler and iPlant, and challenges in implementation.Funded by the National Science Foundation Award #ACI - 144560

Progress report for 2016 and 2017

Summary: From its beginning nearly five years ago, the University of Missouri's CI Council has been guided by faculty with representation from all the schools and colleges. It is important to acknowledge the commitments of time, talent, vision, and perspective toward defining and articulating MU's research cyberinfrastructure priorities and direction. This group has created MU's first CI plan in 2013, and in 2016 refined the plan to call attention to four critical areas: Bioinformatics and Genomics, Geospatial Sciences, Digital Humanities, and Imaging & Visualization. ...Includes "Updates by Semester" in Appendix A

Measuring Success for a Future Vision: Defining Impact in Science Gateways/Virtual Research Environments

Scholars worldwide leverage science gateways/VREs for a wide variety of research and education endeavors spanning diverse scientific fields. Evaluating the value of a given science gateway/VRE to its constituent community is critical in obtaining the financial and human resources necessary to sustain operations and increase adoption in the user community. In this paper, we feature a variety of exemplar science gateways/VREs and detail how they define impact in terms of e.g., their purpose, operation principles, and size of user base. Further, the exemplars recognize that their science gateways/VREs will continuously evolve with technological advancements and standards in cloud computing platforms, web service architectures, data management tools and cybersecurity. Correspondingly, we present a number of technology advances that could be incorporated in next-generation science gateways/VREs to enhance their scope and scale of their operations for greater success/impact. The exemplars are selected from owners of science gateways in the Science Gateways Community Institute (SGCI) clientele in the United States, and from the owners of VREs in the International Virtual Research Environment Interest Group (VRE-IG) of the Research Data Alliance. Thus, community-driven best practices and technology advances are compiled from diverse expert groups with an international perspective to envisage futuristic science gateway/VRE innovations

January 1 - December 31, 2012

This report summarizes training, education, and outreach activities for calendar 2012 of PTI and affiliated organizations, including the School of Informatics and Computing, Office of the Vice President for Information Technology, and Maurer School of Law. Reported activities include those led by PTI Research Centers (Center for Applied Cybersecurity Research, Center for Research in Extreme Scale Technologies, Data to Insight Center, Digital Science Center) and Service and Cyberinfrastructure Centers (Research Technologies Division of University Information Technology Services, National Center for Genome Assembly Support

Report of the 2014 NSF Cybersecurity Summit for Large Facilities and Cyberinfrastructure

This event was supported in part by the National Science Foundation under Grant Number 1234408. Any opinions, findings, and conclusions or recommendations expressed at the event or in this report are those of the authors and do not necessarily reflect the views of the National Science Foundation

High Performance Computing Serving Life Science Research Needs

This talk presents a number of case studies and examples of cyberinfrastructure and science in support of life science research

Performance metrics and auditing framework using application kernels for high‐performance computer systems

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/97468/1/cpe2871.pd

A CyberGIS Integration and Computation Framework for High‐Resolution Continental‐Scale Flood Inundation Mapping

We present a Digital Elevation Model (DEM)-based hydrologic analysis methodology for continental flood inundation mapping (CFIM), implemented as a cyberGIS scientific workflow in which a 1/3rd arc-second (10m) Height Above Nearest Drainage (HAND) raster data for the conterminous U.S. (CONUS) was computed and employed for subsequent inundation mapping. A cyberGIS framework was developed to enable spatiotemporal integration and scalable computing of the entire inundation mapping process on a hybrid supercomputing architecture. The first 1/3rd arc-second CONUS HAND raster dataset was computed in 1.5 days on the CyberGIS ROGER supercomputer. The inundation mapping process developed in our exploratory study couples HAND with National Water Model (NWM) forecast data to enable near real-time inundation forecasts for CONUS. The computational performance of HAND and the inundation mapping process was profiled to gain insights into the computational characteristics in high-performance parallel computing scenarios. The establishment of the CFIM computational framework has broad and significant research implications that may lead to further development and improvement of flood inundation mapping methodologies

Usage of Indiana University computation and data cyberinfrastructure in FY 2011/2012 and assessment of future needs

This report details the past and current cyberinfrastructure resources that have been deployed by the Research Technologies (RT) division of University Information Technologies Services to support research and scholarly activities at IU. This report also presents data and detailed analysis of system usage and services supported by RT for the FY 2011/2012 period, projects future usage trends based on these data, and provides several recommendations for the most effective ways to meet the growing need for high performance computing resources in research and scholarly endeavors.This research was supported in part by: The Pervasive Technology Institute, Indiana Metabolomics and Cytomics Initiative, and the Indiana Genomics Initiative. All of these initiatives have been supported in part by Lilly Endowment, Inc. Grant number 1U24AA014818-01 from NIAAA/NIH. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIAAA/NIH. National Science Foundation under Grants CDA-9601632, EIA-0116050, ACI-0338618l, OCI-0451237, OCI-0535258, and OCI-0504075, CNS-0723054, and CNS-0521433. Shared University Research grants from IBM, Inc. to Indiana University. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the funding agencies represented above