National Center for Genome Analysis Program Year 2 Report – September 15, 2012 – September 14, 2013

On September 15, 2011, Indiana University (IU) received three years of support to establish the National Center for Genome Analysis Support (NCGAS). This technical report describes the activities of the second 12 months of NCGASThe facilities supported by the Research Technologies division at Indiana University are supported by a number of grants. The authors would like to acknowledge that although the National Center for Genome Analysis Support is funded by NSF 1062432, our work would not be possible without the generous support of the following awards received by our parent organization, the Pervasive Technology Institute at Indiana University. • The Indiana University Pervasive Technology Institute was supported in part by two grants from the Lilly Endowment, Inc. • NCGAS has also been supported directly by the Indiana METACyt Initiative. The Indiana METACyt Initiative of Indiana University is supported in part by the Lilly Endowment, Inc. • This material is based in part upon work supported by the National Science Foundation under Grant No. CNS-0521433. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation (NSF)

Solving the Klein-Gordon equation using Fourier spectral methods: A benchmark test for computer performance

The cubic Klein-Gordon equation is a simple but non-trivial partial differential equation whose numerical solution has the main building blocks required for the solution of many other partial differential equations. In this study, the library 2DECOMP&FFT is used in a Fourier spectral scheme to solve the Klein-Gordon equation and strong scaling of the code is examined on thirteen different machines for a problem size of 512^3. The results are useful in assessing likely performance of other parallel fast Fourier transform based programs for solving partial differential equations. The problem is chosen to be large enough to solve on a workstation, yet also of interest to solve quickly on a supercomputer, in particular for parametric studies. Unlike other high performance computing benchmarks, for this problem size, the time to solution will not be improved by simply building a bigger supercomputer.Comment: 10 page

National Center for Genome Analysis Program Year 3 Report – September 15, 2013 – September 14, 2014

On September 15, 2011, Indiana University (IU) received three years of support to establish the National Center for Genome Analysis Support (NCGAS). This technical report describes the activities of the third 12 months of NCGASThe facilities supported by the Research Technologies division at Indiana University are supported by a number of grants. The authors would like to acknowledge that although the National Center for Genome Analysis Support is funded by NSF 1062432, our work would not be possible without the generous support of the following awards received by our parent organization, the Pervasive Technology Institute at Indiana University. • The Indiana University Pervasive Technology Institute was supported in part by two grants from the Lilly Endowment, Inc. • NCGAS has also been supported directly by the Indiana METACyt Initiative. The Indiana METACyt Initiative of Indiana University is supported in part by the Lilly Endowment, Inc. • This material is based in part upon work supported by the National Science Foundation under Grant No. CNS-0521433. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation (NSF)

XSEDE: The Extreme Science and Engineering Discovery Environment (OAC 15-48562) Interim Project Report 13: Report Year 5, Reporting Period 2 August 1, 2020 – October 31, 2020

This is the Interim Project Report 13 (IPR13) for the NSF XSEDE project. It includes Key Performance Indicator data and project highlights for Reporting Year 5, Report Period 2 (August 1-October 31, 2020).NSF OAC 15-48562Ope

2016 eXtreme Science and Engineering Discovery Environment (XSEDE) Annual User Satisfaction Survey

This report provides an analysis and evaluation of the 2016 eXtreme Science and Engineering Discovery Environment (XSEDE) Annual User Satisfaction Survey. Section C.2, describes the data collection methodology of the survey. The sample included 13 types of users in a sample size of 5000 (out of 14,398 users), with 1,007 respondents. The survey consisted of quantitative and qualitative questions designed to determine user satisfaction of XSEDE services and resources. • The survey was available from February 11, 2016 through April 7, 2016. The overall response rate was 22.2%, down from the project high of 27.4% achieved in 2015. • Awareness remained near constant when compared with 2015 results, but with most areas trending slightly upward. • Only one area–Mission–experienced slightly lower awareness. Areas scoring less than 3.0 in terms of awareness where the same as is in 2015: TIS, ECSS, Mobile, Visualization Resources, and Science Gateways. • Data suggests that users are satisfied with XSEDE resources and services ,with all mean satisfaction values significantly greater than 3.0 (on a 5.0 scale) and greater than “4” in most areas. Most areas trended slightly upward or remained the same. • Overall satisfaction with XSEDE remains high at 4.34 on a 5-point scale. This is on par with 2014’s alltime high of 4.36. • Training preferences have remained constant over the 2013-2016 period. Data consistently show preference for self-serve and “just-in-time” training options, (i.e., Web documentation and online, self-paced tutorials.) • Consistent with previous years, demographic analysis shows that a typical user is male, white, and a faculty member at a large, doctoral-granting/research-focused university. Chemistry, physics, and engineering were the primary fields of study for 52% of respondents. • Section D of this report includes all open-ended question responses. Responses are categorizedOpe

Virtualizing the Stampede2 Supercomputer with Applications to HPC in the Cloud

Methods developed at the Texas Advanced Computing Center (TACC) are described and demonstrated for automating the construction of an elastic, virtual cluster emulating the Stampede2 high performance computing (HPC) system. The cluster can be built and/or scaled in a matter of minutes on the Jetstream self-service cloud system and shares many properties of the original Stampede2, including: i) common identity management, ii) access to the same file systems, iii) equivalent software application stack and module system, iv) similar job scheduling interface via Slurm. We measure time-to-solution for a number of common scientific applications on our virtual cluster against equivalent runs on Stampede2 and develop an application profile where performance is similar or otherwise acceptable. For such applications, the virtual cluster provides an effective form of "cloud bursting" with the potential to significantly improve overall turnaround time, particularly when Stampede2 is experiencing long queue wait times. In addition, the virtual cluster can be used for test and debug without directly impacting Stampede2. We conclude with a discussion of how science gateways can leverage the TACC Jobs API web service to incorporate this cloud bursting technique transparently to the end user.Comment: 6 pages, 0 figures, PEARC '18: Practice and Experience in Advanced Research Computing, July 22--26, 2018, Pittsburgh, PA, US

XSEDE 12 Conference Final Report

XSEDE 2012 conference final repor