DOCSLIB.ORG

SHIFTING MODALITIES of USE in the XSEDE PROJECT Richard Knepper Submitted to the Faculty of the University Graduate School in Pa

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
SHIFTING MODALITIES of USE in the XSEDE PROJECT Richard Knepper Submitted to the Faculty of the University Graduate School in Pa SHIFTING MODALITIES OF USE IN THE XSEDE PROJECT Richard Knepper Submitted to the faculty of the University Graduate School in partial fulfillment of the requirements for the degree Doctor of Philosophy in the School of Informatics and Computing Indiana University May, 2017 ProQuest Number:10277697 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. ProQuest 10277697 Published by ProQuest LLC ( 2017). Copyright of the Dissertation is held by the Author. All rights reserved. This work is protected against unauthorized copying under Title 17, United States Code Microform Edition © ProQuest LLC. ProQuest LLC. 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, MI 48106 - 1346 Accepted by the Graduate Faculty, Indiana University, in partial fulfillment of the requirements for the degree of Doctor of Philosophy. Doctoral Committee: Nathan Ensmenger, PhD Christena Nippert-Eng, PhD Katy Borner,¨ PhD Kosali Simon, PhD April 25, 2017 ii For Ula, who always championed me through setbacks and successes. For Dick, who always provided the hardest questions. For David, who always asked “Now, how do we get you out of here?” iii Acknowledgements This dissertation is the product of a particular set of experiences in time, which were afforded to me by my concurrent role as a professional IT manager working in the XSEDE project and as a student curious about organizations, technology, and scientists. I could not have had the access, frankness, and trust that I was able to achieve without the openness and interest of the members of the XSEDE project, its staff, management, and users. I especially thank XSEDE principal investigator John Towns, who took the time to read associated papers and discuss the project with me while in the middle of running a multimillion-dollar project distributed across fifteen partner institutions, and XSEDE’s NSF Program Director Rudolf Eigenmann, who provided me a view of the NSF processes behind the organization. Data for the quantitative investigations that made up part of this project were made available thanks to Dave Hart of the Na- tional Center for Atmospheric Research for providing publications infor- mation from the XSEDE portal and discussing utilization and publication information, and also to Robert Deleon and Tom Furlani of the University of Buffalo for providing XSEDE project and usage data. As an interview respondent, Dr. Craig Stewart provided excellent material as well as ad- vice during the preparation of this research. This project would not have been possible to bring to completion with- out its research committee. Dr. Nathan Ensmenger provided unwavering support and assurance throughout the process of developing the area of inquiry and the points of interest which came out of my conversations with informants. Dr. Christena Nippert-Eng was a source of guidance on matters ethnological as well as in the drafting stages of this dissertation. Dr. Katy Borner¨ informed and instructed on the quantitative and network science portions of the research. Dr. Kosali Simon provided insight into policy matters and the policymaker perspective. The work below would not have been possible without the guidance and support of the late David Hakken, who provided intellectual guidance and questions which provided the foundations of inquiry. David was a credit to his field and always supported those investigators who looked at the unusual, the failures, and the imbalances in our world. iv Richard Knepper Shifting Modalities of Use in the XSEDE Project The National Science Foundation’s Extreme Science and Engineering Discovery Environment (XSEDE) provides a broad range of computational resources for researchers in the United States. While the model of com- putational service provision that XSEDE provides suits a traditional high performance computing model well, there are some indications that com- putational research is moving to new modalities of use and new virtual organizations. This ethnography of the users, management, and staff of XSEDE explores how a large virtual organization is charged with pro- viding both next-generation computational resources and reaching out to a broader community which is just beginning to embrace computa- tional techniques. The challenges of balancing the demands of a diverse set of stakeholders, the guidance of changing leadership at the NSF, and managing the development and professionalization of the cyberinfrastruc- ture workforce create a number of tensions and dynamics. This research project identifies how these dynamics arise and are resolved, reflecting on the science policy initiatives which define and constrain the environment. In addition to ethnographic description of the project and interview analy- sis, social network analyses of the XSEDE user base and research project usage information are conducted, showing a collection of traditional HPC users and support for research from traditional research oriented institu- tions, rather than extending to new, broader communities. Nathan Ensmenger, PhD Christena Nippert-Eng, PhD Katy Borner,¨ PhD Kosali Simon, PhD v Contents Dedication iii Acknowledgements iv Abstract v 1 Introduction 1 1.1 Central Questions ......................... 6 1.2 Motivation .............................. 10 1.2.1 Informing studies of scientific collaboration ...... 11 1.2.2 Understanding relationships between infrastructure and research ........................... 13 1.2.3 Informing science policy and NSF initiatives ...... 18 1.3 Key Concepts ............................ 19 1.3.1 Cyberinfrastructure and the CI community ...... 20 1.3.2 Government-sponsored cyberinfrastructure environment 32 2 Literature Review 40 2.1 Studies of Cyberinfrastructure .................. 40 2.1.1 The roots of cyberinfrastructure within Big Science . 40 2.1.2 The development of collaborative cyberinfrastructure 53 2.1.3 Literature on cyberinfrastructure usage and scientific production ......................... 59 2.2 Science Policy ........................... 62 2.2.1 Government funding for basic research . ....... 64 2.2.2 Making Grants Measurable ................ 71 2.2.3 The competitive element .................. 75 2.2.4 Public Management Networks for Service Delivery . 77 vi 3 NSF-funded cyberinfrastructure prior to XSEDE 87 3.1 The NSF Supercomputing Centers Program . ....... 88 3.2 The TeraGrid ............................ 91 3.2.1 TeraGrid innovations ................... 93 3.2.2 TeraGrid Metrics and Incentives ............. 100 3.2.3 TeraGrid tensions and dynamics ............. 104 4 Research Methods 112 4.1 Investigator Statement ...................... 113 4.2 Qualitative Analyses ........................ 116 4.2.1 Document Analysis .................... 117 4.2.2 Interviews .......................... 119 4.2.3 Ethnographic Observations ................ 125 4.3 Quantitative Analyses ....................... 129 4.3.1 Data Gathering ....................... 130 4.3.2 Bibliometric Analysis ................... 133 4.3.3 Analysis of usage data ................... 134 4.4 Institutional Review ........................ 135 5 Findings 136 5.1 From TeraGrid to XSEDE ..................... 137 5.1.1 The XD solicitation ..................... 137 5.1.2 The “shotgun wedding” .................. 140 5.1.3 XSEDE operations begin: the move towards service . 144 5.2 Understanding XSEDE users ................... 155 5.2.1 Changing fields of science in XSEDE . ....... 155 5.2.2 The “Long Tail” of XSEDE ................. 159 5.2.3 How users leverage XSEDE ................ 167 5.2.4 Researcher tactics ..................... 170 5.3 Understanding XSEDE and the CI community . ....... 175 5.3.1 Cyberinfrastructure Crises ................ 178 5.3.2 Adaptations in the Virtual Organization . ....... 181 6 Conclusions 185 6.1 Cyberinfrastructure trends .................... 186 6.2 XSEDE 2 and what comes after ................. 189 6.3 Science Policy lessons ....................... 193 6.4 Areas for further research .................... 195 vii Bibliography 197 A Interview Questions 215 Curriculum Vitae viii Chapter 1 Introduction Scientific research requires tools and instruments in order to conduct ex- periments, make measurements, and calculate results. As scientific stud- ies have moved from individual to group efforts and technological change has moved scientific work from the laboratory to the computer, the pri- mary instrument of inquiry has become the computer. Joint scientific work which is mediated by the Internet is increasingly the normal form of scientific inquiry [59]. With the development of these “collaboratories” as described by Finholt and Olsen [61], the work of scientists increas- ingly becomes more collaborative, both in terms of direct collaboration with co-authors as well as indirectly, with other researchers who develop scientific software, technicians and engineers who manage instruments and systems, administrative staff who oversee project work, and granting agency program officers who determine funding levels and manage solic- itations for projects. Obtaining and managing computational resources has become a key component of a number of disciplines’ research ac- tivities, and the need for computationally-skilled scientists seems to be 1 more urgent than ever. For some, computational methods represent
Load more

Recommended publications
  • Keynote Speaker-2 How I Became a Computational Scientist
    Keynote Speaker-2 How I Became a Computational Scientist J. Mailen Kootsey Redlands, California, USA Email: [email protected] Abstract— Professional journal advertisements, email newsletters, and university marketing now advertise numerous educational and research programs in computational physics, computational biology, and other fields where computation is an essential element of the discipline. These programs all have very recent origins, made possible by the exponential growth in the availability of compute power. In this presentation, I describe some milestones in my own experience as a person living through and participating in the birth of computational science – especially the contributions of computing to scientific theory and understanding. I began my history with analog computing, learned numerical methods by manual computations of derivatives and integrals, learned to program an early vacuum tube computer, and experienced challenges in finding acceptance for computer methods in traditional biomedical disciplines. Keywords—computational science, history of science, biomedicine, cardiac electrophysiology, analog computer, numerical methods. 1. Introduction : Computers are now making major contributions to all fields of science, from fundamental particle physics through chemistry, biology, and medicine, to the social sciences and cosmology. A major part of the computer contribution to these fields is related to data: acquisition, organization, presentation, sharing, and pattern recognition in data. Computers are also changing scientific theory by making it possible to explore and evaluate models that are much more realistic and complex than could be considered with only analytic and hand calculations. Computational science did not spring into existence fully developed, but experienced birth and development like a living system. In some scientific fields, the contribution of computing to theory is still in early stages.
    [Show full text]
  • Computational Scientist Tracking Code 3624 Job Description
    Computational Scientist Tracking Code 3624 Job Description Assistant Computational Scientist/Associate Computational Scientist/Computational Scientist in Computational Sciences-Statistics & Analytics Group The Jackson Laboratory of Genomic Medicine, based in Farmington, CT is seeking computational scientists of all levels to join our Computational Sciences – Statistics & Analytics (CS-SA) group. These positions offer the opportunity to make leading contributions to cutting edge research in mouse genetics, disease biology, and translational research in collaboration with the faculty and genetic resource scientists and clients of The Jackson Laboratory (JAX). Cross campus and industry collaborations are encouraged. These positions report to the Director of Jackson’s Computational Sciences (CS) team and have primary responsibility for providing statistical and analytical bioinformatics expertise and interpretation to the scientific research programs at the Jackson Laboratory for Genomic Medicine in Farmington, CT and its collaborative programs. Characteristic distinction from Assistant Computational Scientist to Associate Computational Scientist to Computational Scientist include increased ability to work independently, development of in-depth knowledge in selected biological disciplines to analyze and provide expert reasoning to the relevant projects. A Computational Scientist is expected to independently establish collaborations within JAX, providing expert reasoning to the projects relevant to his disciplines and make leading contributions
    [Show full text]
  • Algorithmic Social Sciences Research Unit ASSRU
    Algorithmic Social Sciences Research Unit ASSRU Department of Economics University of Trento Via Inama 5 381 22 Trento Italy Discussion Paper Series 11 – 06 HOW SHALL WE PREPARE STUDENTS FOR ATTACKING NEW SCIENTIFIC PROBLEMS WITH COMPUTATION? Rosalind Reid1 March 2011 1 Executive Director, Institute for Applied Computational Science, Harvard School of Engineering and Applied Sciences, 29 Oxford Street, Cambridge, MA 02138 USA. [email protected] Abstract Computation is making its way into the mainstream of natural and social science research by fits and starts. “Computational science,” once a toolkit, is emerging as a fundamentally new approach to exploration and hypothesis formation as well as analysis. It is not yet clear, however, just how computation will make novel contributions and change the nature (not just the methodology) of science. Harvard is engaged in creating a program that may test new ideas about how scholars should be trained. The rising dominance of large computation means, for example, that scholars must work in large and interdisciplinary groups in the future. And to advance the field, they must learn what it means to make a scientific question computable.What preparation will enable them to create this new field? This article reports on discussions toward establishing a new curriculum at Harvard and observations of the experience of similar programs at Stanford. 1 Introduction: What is computational science? Science (whether natural or social) advances by continually testing and refining models of the world—falsifiable, simplifying statements (“x is a function of y”) put forward to explain how things work. The traditional scientific method tests those models against data from experiments and observations.
    [Show full text]
  • AETA-Computational-Engineering.Pdf
    Computational Engineering A Agent-based computational economics Algorithmic art Artificial intelligence Astroinformatics Author profiling B Biodiversity informatics Biological computation C Cellular automaton Chaos theory Cheminformatics Code stylometry Community informatics Computable topology Computational aeroacoustics Computational archaeology Computational astrophysics Computational auditory scene analysis Computational biology Computational chemistry Computational cognition Computational complexity theory Computational creativity Computational criminology Computational economics Computational electromagnetics Computational epigenetics Computational epistemology Computational finance Computational fluid dynamics Computational genomics Computational geometry Computational geophysics Computational group theory Computational humor Computational immunology Computational journalism Computational law Computational learning theory Computational lexicology Computational linguistics Computational lithography Computational logic Computational magnetohydrodynamics Computational Materials Science Computational mechanics Computational musicology Computational neurogenetic modeling Computational neuroscience Computational number theory Computational particle physics Computational photography Computational physics Computational science Computational engineering Computational scientist Computational semantics Computational semiotics Computational social science Computational sociology Computational
    [Show full text]
  • CAFCW20 Presenters
    CAFCW20 Presenters Devanshu Agrawal, University of Tennessee, Knoxville Devanshu Agrawal is a PhD student in the Data Science and Engineering program in the Bredesen Center at the University of Tennessee, Knoxville and works as a research assistant in the Computational Sciences and Engineering division at Oak Ridge National Laboratory. He received bachelor’s degrees in mathematics and physics and a master’s degree in mathematics from East Tennessee State University, where he taught calculus after that. Agrawal’s research focuses on the theory and applications of Bayesian deep learning. Paul Aiyetan, MD, Frederick National Laboratory for Cancer Research Dr. Paul Aiyetan obtained his MD from the College of Medicine, University of Ibadan. He completed his intern year as a house physician at the University College Hospital and the next two years as a resident medical officer. He earned a Master of Science degree in bioinformatics from Johns Hopkins University and a PhD from the George Mason University School of Systems Biology. After a graduate fellowship in oncology, bioinformatics and biostatistics, Dr. Aiyetan completed a postdoctoral fellowship in pathology at the Johns Hopkins University School of Medicine where he was a member of the NIH/NCI-funded Clinical Proteomics Tumor Analysis Consortium. He was also a member of the NIH/NHLBI-funded Programs of Excellence in Glycosciences (PEG). He received the Johns Hopkins Pathology Young Investigators Excellence Award and the inaugural NIH-funded Big Data to Knowledge fellowship at the University of Minnesota and the Mayo Clinic. Dr. Aiyetan’s research interest is at the intersection of medicine, computational biology and quantitative science, investigating physical and biochemical science principles and computational and quantitative methods to elucidate mechanism of disease processes, particularly neoplastic processes (cancer), with an aim to identify and develop more precise diagnostic and therapeutic approaches.
    [Show full text]
  • Undergraduate Computational Science and Engineering Education
    Undergraduate Computational Science and Engineering Education SIAM Working Group on CSE Undergraduate Education, Peter Turner, Chair Contact address: Mathematics & Computer Science Clarkson University, Potsdam NY 13699-5815 [email protected] September 20, 2006 1Introduction In many areas of science and engineering, computation has become an equal and indispensable partner, along with theory and experiment, in the quest for knowledge and the advancement of technology. Numerical simulation enables the study of complex systems and natural phenomena that would be too expen- sive or dangerous, or even impossible, to study by direct experimentation. An increase during the past 30 years of over six orders of magnitude in computer speed, and another six orders of magnitude in algorithm speed, along with ad- vances in mathematics in understanding and modeling complex systems, and in computer science of manipulating and visualizing large amounts of data, has en- abled computational scientists and engineers to solve large-scale problems that were once thought intractable. Why should you introduce an undergraduate CSE program at your school? There are at least four fundamental reasons. All of these will be expanded upon in subsequent sections of this report. 1. Computational science and engineering (CSE) is a rapidly growing multi- disciplinary area with connections to the sciences, engineering, mathemat- ics and computer science. CSE focuses on the development of problem- solving methodologies and robust tools for the solution of scientificand engineering problems. We believe that CSE will play an important if not dominating role for the future of the scientific discovery process and engineering design. 2. It is widely documented that the number and proportion of female under- graduates in computing fields has been declining over recent years.
    [Show full text]
  • Conservation of Computational Scientific Execution Environments
    Departamento de Inteligencia Artificial Escuela Técnica Superior de Ingenieros Informáticos PhD Thesis Conservation of Computational Scientific Execution Environments for Workflow-based Experiments Using Ontologies Author: Idafen Santana Pérez Supervisors: Prof. Dra. María Pérez Hernández Prof. Dr. Oscar Corcho January, 2016 ii Tribunal nombrado por el Sr. Rector Magfco. de la Universidad Politécnica de Madrid, el día 18 de Enero de 2016. Presidente: Dra. Asunción Gómez Pérez Vocal: Dr. Erick Antezana Vocal: Dr. Alexander García Vocal: Dr. Jesús Carretero Secretario: Dr. Rubén Montero Suplente: Dr. Mariano Fernández López Suplente: Dr. Alberto Sánchez Campos Realizado el acto de defensa y lectura de la Tesis el día 22 de Enero de 2016 en la Escuela Técnica Superior de Ingenieros Informáticos Calificación: EL PRESIDENTE VOCAL 1 VOCAL 2 VOCAL 3 EL SECRETARIO iii iv A Gina y Carlos. AIsa. v vi Agradecimientos And now, the end is near, and so I face this final curtain, I have to take a moment to thank all the people that I found along the way, that have helped me in this journey. From research colleagues, to friend and family, many people have contributed to this thesis, both at the professional and personal level. First of all, I would like to thank my advisors, María Pérez and Oscar Corcho, for guiding and supporting me all these years, allowing me to find my own path in my research career, and helping me whenever I needed it. As well I would like to thank Asunción Gómez Pérez, for the leading role she has played in our group during these years.
    [Show full text]
  • Curriculum Vitae Sharon Hammes-Schiffer Date of Birth
    Curriculum Vitae Sharon Hammes-Schiffer Department of Chemistry phone: (203) 436-3936 Yale University 225 Prospect Street e-mail: [email protected] New Haven, CT 06520-8107 http://hammes-schiffer-group.org/ Date of Birth May 27, 1966 Education B.A. Chemistry Princeton University 5/88 summa cum laude, Highest Honors in Chemistry Ph.D. Chemistry Stanford University 9/93 Graduate advisor: Hans C. Andersen Professional Experience John Gamble Kirkwood Professor of Chemistry 1/18 – present Yale University Swanlund Professor of Chemistry 8/12 − 12/17 University of Illinois at Urbana-Champaign Eberly Professor in Biotechnology 8/06 − 8/12 Pennsylvania State University Professor of Chemistry 7/03 − 8/12 Pennsylvania State University Shaffer Associate Professor of Chemistry 8/00 − 7/03 Pennsylvania State University Clare Boothe Luce Assistant Professor of Chemistry 8/95 − 8/00 University of Notre Dame Postdoctoral research scientist AT&T Bell Laboratories 9/93 − 8/95 AT&T Bell Laboratories, Murray Hill, NJ Postdoctoral supervisor: John C. Tully Honors and Awards G. M. Kosolapoff Award from Auburn University, 2019 Honorary Fellow, Chinese Chemical Society, 2018 Member, Connecticut Academy of Science and Engineering (CASE), 2018 Center for Advanced Study Professor, University of Illinois Urbana-Champaign, 2017 Senior Fellow, Canadian Institute for Advanced Research (CIFAR), 2016 − present Fellow, Biophysical Society, 2015 Blue Waters Professor, 2014 – 2018 Member, International Academy of Quantum Molecular Science, 2014 Member, U.S. National Academy of Sciences, 2013 Fellow, American Association for the Advancement of Science, 2013 Member, American Academy of Arts and Sciences, 2012 Fellow, American Chemical Society, 2011 1 Sharon Hammes-Schiffer CV -- 02/10/19 National Institutes of Health MERIT Award, 2011 Fellow, American Physical Society, 2010 American Chemical Society Akron Section Award, 2008 International Academy of Quantum Molecular Science Medal, 2005 Iota Sigma Pi Agnes Fay Morgan Research Award, 2005 Alexander M.
    [Show full text]
  • What Can I Do with a Major in Physics
    Physics, the science of matter and energy, is the study of the deepest mysteries of our universe, ranging from the smallest subatomic particles to the largest galaxies in the universe. Exploring ideas of space, time, matter, energy, and radiation, physics serves as the basis for the physical sciences. Today’s society is influenced by physics in countless ways, including recent developments in such fields as laser optics, miniaturized electronics, nuclear energy, and medical instrumentation. Astronomy applies the ideas of physics to the study of planets, stars, galaxies, and all celestial phenomena within reach of our telescopes. University of Wisconsin–Eau Claire offers standard majors in liberal arts, applied physics, dual degree (for engineering), and physics teaching, as well as comprehensive majors in physical science and physics–mathematics. In addition to these majors, UW–Eau Claire offers minors in liberal arts and physics teaching. Typical interests and values of physics majors: Gathering information • Handling details Gaining knowledge about our physical Initiating new ideas • Defining needs environment Imagining alternatives • Problem Solving Analyzing and sharing experimental data Designing projects/experiments Related student and professional organizations: Working with optical, electronic, and Student: computational equipment Society of Physics Students Solving the mysteries of our complicated universe Sigma Pi Sigma–Physics Honor Society Chippewa Valley Astronomical Society Knowledge and skills gained from studying physics: Knowledge: Professional: Students who are pursuing a degree in physics learn American Physical Society how to solve quantitative problems and find American Institute of Physics relationships between physical factors. Physics majors Institute of Physics can organize, analyze, and interpret scientific data. Acoustical Society of America They develop knowledge of natural laws of optical, American Astronomical Society mechanical, and electrical data.
    [Show full text]
  • 1 the Attendee Registration Form Is Located At
    UNITED STATES OF AMERICA FEDERAL ENERGY REGULATORY COMMISSION Increasing Market and Planning Efficiency Docket No. AD10-12-012 through Improved Software SUPPLEMENTAL NOTICE OF TECHNICAL CONFERENCE ON INCREASING REAL- TIME AND DAY-AHEAD MARKET EFFICIENCY THROUGH IMPROVED SOFTWARE (May 28, 2021) As first announced in the Notice of Technical Conference issued in this proceeding on March 11, 2021, Commission staff will convene a technical conference on June 22, 23, and 24, 2021 to discuss opportunities for increasing real-time and day-ahead market efficiency of the bulk power system through improved software. Attached to this Supplemental Notice is an agenda for the technical conference and speakers’ summaries of their presentations. While the intent of the technical conference is not to focus on any specific matters before the Commission, some conference discussions might include topics at issue in proceedings that are currently pending before the Commission, including topics related to capacity valuation methodologies for renewable, hybrid, or storage resources. These proceedings include, but are not limited to: PJM Interconnection, L.L.C. Docket No. ER20-584-000 PJM Interconnection, L.L.C. Docket No. EL19-100-000 PJM Interconnection, L.L.C. Docket Nos. ER21-278-000 and ER21-278- 001 The conference will take place virtually via WebEx, with remote participation from both presenters and attendees. Further details on remote attendance and participation will be released prior to the conference. Attendees must register through the Commission’s website on or before June 11, 2021.1 WebEx connections may not be available to those who do not register. The Commission will accept comments following the conference, with a deadline of July 30, 2021.
    [Show full text]
  • A Science-Based Case for Large-Scale Simulation
    A SCIENCE-BASED CASE FOR LARGE-SCALE SIMULATION Office of Science U.S. Department of Energy July 30, 2003 “There will be opened a gateway and a road to a large and excellent science, into which minds more piercing than mine shall penetrate to recesses still deeper.” Galileo (1564–1642) [on the “experimental mathematical analysis of nature,” appropriated here for “computational simulation”] TRANSMITTAL July 30, 2003 Dr. Raymond L. Orbach, Director Office of Science U.S. Department of Energy Washington, DC Dear Dr. Orbach, On behalf of more than 300 contributing computational scientists from dozens of leading universities, all of the multiprogrammatic laboratories of the Department of Energy, other federal agencies, and industry, I am pleased to deliver Volume 1 of a two-volume report that builds a Science-Based Case for Large-Scale Simulation. We find herein (and detail further in the companion volume) that favorable trends in computational power and networking, scientific software engineering and infrastructure, and modeling and algorithms are allowing several applications to approach thresholds beyond which lies new knowledge of both fundamental and practical kinds. A major increase in investment in computational modeling and simulation is appropriate at this time, so that our citizens are the first to benefit from particular new fruits of scientific simulation, and indeed, from an evolving culture of simulation science. Based on the encouraging first two years of the Scientific Discovery through Advanced Computing initiative, we believe that balanced investment in scientific applications, applied mathematics, and computer science, with cross-accountabilities between these constituents, is a program structure worthy of extension.
    [Show full text]
  • Television Over the Internet
    International Journal of Trend in Research and Development, Volume 6(4), ISSN: 2394-9333 www.ijtrd.com Computational Science 1Matthew N. O. Sadiku, 2Kelechi G. Eze and 3Sarhan M. Musa, 1,2,3Roy G. Perry College of Engineering, Prairie View A&M University, Prairie View, TX, United States Abstract: Computational science refers to the use of computer A computational scientist is usually a scientist, an engineer hardware and software to solve scientific problems in diverse or an applied mathematician who is skilled in scientific areas such as sciences, engineering, finance, and humanities. It computing, programming languages, operating systems is at the intersection of mathematics, computer science, and the visualization software, and parallel computing. Common core disciplines of science and engineering. It has become an numerical techniques used by computational scientists include indispensable partner along with theory and experiment. It is finite elements, moment methods, finite difference method, crucial to the security and welfare of any nation. It is becoming Monte Carlo methods, methods of integration, and methods of indispensable in many scientific investigations ranging from line. chemistry, physics, mathematics, engineering, economics, and II. APPLICATIONS finance. This paper provides a brief introduction to computational science. Many disciplines have undergone a computational turn in the past decades. The recent computational turn has produced sub- Keywords: Computational Science, Computational Science disciplines such as computational biology, computational and Engineering, Computational Methods, Scientific chemistry, computational physics, and computational finance. Computing Computational Biology: This is the science of modeling I. INTRODUCTION biological systems. Computational techniques are Since the invention of digital computer, its potential to aid revolutionizing biology.
    [Show full text]