@inBook{
 title = {Cyberinfrastructure, Cloud Computing, Science Gateways, Visualization, and Cyberinfrastructure Ease of Use},
 type = {inBook},
 year = {2019},
 identifiers = {[object Object]},
 pages = {157-170},
 websites = {http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-7598-6.ch012},
 publisher = {IGI Global},
 city = {Hershey, PA, USA},
 editors = {[object Object]},
 id = {68b708e4-1b2e-35e8-a3fb-75ae09b4a0a5},
 created = {2019-08-15T19:24:16.885Z},
 file_attached = {false},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 group_id = {0e433c5b-85c4-32aa-851c-c145aac9f80f},
 last_modified = {2019-08-27T14:14:28.997Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 source_type = {CHAP},
 private_publication = {false},
 abstract = {Computers accelerate our ability to achieve scientific breakthroughs. As technology evolves and new research needs come to light, the role for cyberinfrastructure as “knowledge” infrastructure continues to expand. In essence, cyberinfrastructure can be thought of as the integration of supercomputers, data resources, visualization, and people that extends the impact and utility of information technology. This chapter discusses cyberinfrastructure, the related topics of science gateways and campus bridging, and identifies future challenges and opportunities in cyberinfrastructure.},
 bibtype = {inBook},
 author = {Stewart, Craig A and Knepper, Richard and Link, Matthew R and Pierce, Marlon and Wernert, Eric and Wilkins-Diehr, Nancy},
 book = {Advanced Methodologies and Technologies in Network Architecture, Mobile Computing, and Data Analytics}
}

Computers accelerate our ability to achieve scientific breakthroughs. As technology evolves and new research needs come to light, the role for cyberinfrastructure as “knowledge” infrastructure continues to expand. In essence, cyberinfrastructure can be thought of as the integration of supercomputers, data resources, visualization, and people that extends the impact and utility of information technology. This chapter discusses cyberinfrastructure, the related topics of science gateways and campus bridging, and identifies future challenges and opportunities in cyberinfrastructure.

@inProceedings{
 title = {The USD Science Gateway},
 type = {inProceedings},
 year = {2019},
 identifiers = {[object Object]},
 pages = {1-4},
 websites = {http://dl.acm.org/citation.cfm?doid=3332186.3333254},
 publisher = {ACM Press},
 city = {New York, New York, USA},
 id = {c138994c-8dc7-3c35-a93a-80a0583037a9},
 created = {2019-08-15T21:24:32.397Z},
 accessed = {2019-08-15},
 file_attached = {true},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 group_id = {0e433c5b-85c4-32aa-851c-c145aac9f80f},
 last_modified = {2019-09-12T17:32:38.345Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Science Gateways are virtual environments that accelerate scientific discovery by enabling scientific communities to more easily and effectively utilize distributed computing and data resources. Successful Science Gateways provide access to sophisticated and powerful resources, while shielding their users from the underlying complexities. Here we present updated work completed by the University of South Dakota (USD) Research Computing Group in conjunction with the Science Gateways Community Institute (SGCI) [1] and Science Gateways Research Center at Indiana University to set up a Science Gateway to access USD's high-performance computing resources. We also introduce improvements to the system since the previous presentation of our work. These resources are now available to both faculty and students and allow ease of access and use of USD's distributed computing and data resources. The implementation of this gateway project has been multifaceted and has included placement of federated user login, user facilitation and outreach, and integration of USD's cyberinfrastructure resources. We present this project as an example for other research computing groups so that they may learn from our successes and the challenges that we have overcome in providing this user resource. Additionally, this project serves to exemplify the importance of creating a broad user base of research computing infrastructure through the development of alternative user interfaces such as Science Gateways.},
 bibtype = {inProceedings},
 author = {Kleinsasser, Adison A. and Pamidighantam, Sudhakar and Jennewein, Douglas M. and Madison, Joseph D. and Christie, Marcus and Abeysinghe, Eroma and Marru, Suresh and Pierce, Marlon},
 booktitle = {Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning) - PEARC '19}
}

Science Gateways are virtual environments that accelerate scientific discovery by enabling scientific communities to more easily and effectively utilize distributed computing and data resources. Successful Science Gateways provide access to sophisticated and powerful resources, while shielding their users from the underlying complexities. Here we present updated work completed by the University of South Dakota (USD) Research Computing Group in conjunction with the Science Gateways Community Institute (SGCI) [1] and Science Gateways Research Center at Indiana University to set up a Science Gateway to access USD's high-performance computing resources. We also introduce improvements to the system since the previous presentation of our work. These resources are now available to both faculty and students and allow ease of access and use of USD's distributed computing and data resources. The implementation of this gateway project has been multifaceted and has included placement of federated user login, user facilitation and outreach, and integration of USD's cyberinfrastructure resources. We present this project as an example for other research computing groups so that they may learn from our successes and the challenges that we have overcome in providing this user resource. Additionally, this project serves to exemplify the importance of creating a broad user base of research computing infrastructure through the development of alternative user interfaces such as Science Gateways.

@inProceedings{
 title = {InterACTWEL Science Gateway for Adaptation Planning in Food-Energy-Water Sectors of Local Communities},
 type = {inProceedings},
 year = {2019},
 identifiers = {[object Object]},
 pages = {1-4},
 publisher = {Association for Computing Machinery (ACM)},
 id = {ba0e9b5b-a3f7-325c-8399-1cb33bbe7104},
 created = {2019-08-19T14:44:39.569Z},
 accessed = {2019-08-19},
 file_attached = {true},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 group_id = {0e433c5b-85c4-32aa-851c-c145aac9f80f},
 last_modified = {2019-08-27T14:14:28.803Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Since their inception in mid 2000s, adoption of Science Gateways as interfaces and conduits for digital infrastructure needed in science and engineering research and education has significantly increased. This trend has also driven changes in the types of services and resources that are now being expected from the Science Gateways by a growing group of diverse end users. In this poster, we present a novel Science Gateway, InterACTWEL (Interactive Adaptation and Collaboration Tool for managing Water, Energy and Land), which serves as a research cyberinfrastructure as well as an applied decision support system for adaptive natural resources management in interdependent food, energy, and water sectors. End users of this gateway include not only interdisciplinary technical and social science researchers, but also public and private sectoral stakeholders. The gateway is a collaboration between Oregon State University and Science Gateways Research Center, Pervasive Technology Institute at Indiana University, and is addressing challenges and solutions related to computational services, visualization techniques, advanced software applications, collaboration capabilities, cyber security and privacy, and data repositories unique to food-energy-water sectors and their stakeholders.},
 bibtype = {inProceedings},
 author = {Babbar-Sebens, Meghna and Rivera, Samuel and Abeysinghe, Eroma and Marru, Suresh and Pierce, Marlon and Coulter, Eric and Farahani, Majid and Wannipurage, Dimuthu and Christie, Marcus},
 booktitle = {Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning) - PEARC '19}
}

Since their inception in mid 2000s, adoption of Science Gateways as interfaces and conduits for digital infrastructure needed in science and engineering research and education has significantly increased. This trend has also driven changes in the types of services and resources that are now being expected from the Science Gateways by a growing group of diverse end users. In this poster, we present a novel Science Gateway, InterACTWEL (Interactive Adaptation and Collaboration Tool for managing Water, Energy and Land), which serves as a research cyberinfrastructure as well as an applied decision support system for adaptive natural resources management in interdependent food, energy, and water sectors. End users of this gateway include not only interdisciplinary technical and social science researchers, but also public and private sectoral stakeholders. The gateway is a collaboration between Oregon State University and Science Gateways Research Center, Pervasive Technology Institute at Indiana University, and is addressing challenges and solutions related to computational services, visualization techniques, advanced software applications, collaboration capabilities, cyber security and privacy, and data repositories unique to food-energy-water sectors and their stakeholders.

@inProceedings{
 title = {LSU Computational System Biology Gateway for Education},
 type = {inProceedings},
 year = {2019},
 identifiers = {[object Object]},
 pages = {1-4},
 websites = {http://dl.acm.org/citation.cfm?doid=3332186.3333259},
 publisher = {ACM Press},
 city = {New York, New York, USA},
 id = {11ef89c5-a63a-3627-ac30-41371d3e4431},
 created = {2019-08-19T14:45:42.294Z},
 accessed = {2019-08-19},
 file_attached = {true},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 group_id = {0e433c5b-85c4-32aa-851c-c145aac9f80f},
 last_modified = {2019-09-12T17:32:37.962Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Science gateways are a mechanism for delivering scientific software as a service, especially when the software requires high performance computing (HPC) resources to run effectively. The existence of a science gateway eliminates the user's need to learn to work with HPC systems and to manage software installations and updates. With well-designed user interfaces, users can more quickly become effective users of scientific applications and can manage information needed for replicating, modifying, and sharing results. All of these efficiency gains enable users to focus more on their research. In addition, science gateways are being identified as an effective educational tool, a tool to be used in classroom environments as a method to get students quickly into research on domain specific questions. In the absence of a science gateway, students are likely to need a considerable time to learn to work with HPC systems, and any time spent on such will reduce their time on the actual science. This poster presents how the Louisiana State University (LSU) gateway for the Computational System Biology Group (CSBG) - (www.brylinski.org) was updated and improved to be a classroom teaching tool. This work makes extensive use of Apache Airavata's group management capabilities.},
 bibtype = {inProceedings},
 author = {Abeysinghe, Eroma and Brylinski, Michal and Christie, Marcus and Marru, Suresh and Pierce, Marlon},
 booktitle = {Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning) - PEARC '19}
}

Science gateways are a mechanism for delivering scientific software as a service, especially when the software requires high performance computing (HPC) resources to run effectively. The existence of a science gateway eliminates the user's need to learn to work with HPC systems and to manage software installations and updates. With well-designed user interfaces, users can more quickly become effective users of scientific applications and can manage information needed for replicating, modifying, and sharing results. All of these efficiency gains enable users to focus more on their research. In addition, science gateways are being identified as an effective educational tool, a tool to be used in classroom environments as a method to get students quickly into research on domain specific questions. In the absence of a science gateway, students are likely to need a considerable time to learn to work with HPC systems, and any time spent on such will reduce their time on the actual science. This poster presents how the Louisiana State University (LSU) gateway for the Computational System Biology Group (CSBG) - (www.brylinski.org) was updated and improved to be a classroom teaching tool. This work makes extensive use of Apache Airavata's group management capabilities.

@inProceedings{
 title = {The Distant Reader},
 type = {inProceedings},
 year = {2019},
 identifiers = {[object Object]},
 pages = {1-4},
 websites = {http://dl.acm.org/citation.cfm?doid=3332186.3333260},
 publisher = {ACM Press},
 city = {New York, New York, USA},
 id = {b60c0c89-d701-3aea-87e8-0cc135bf5119},
 created = {2019-08-19T14:46:24.989Z},
 accessed = {2019-08-19},
 file_attached = {true},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 group_id = {0e433c5b-85c4-32aa-851c-c145aac9f80f},
 last_modified = {2019-09-12T18:48:08.623Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The Distant Reader science gateway can be used to automatically create and analyze text corpora at a scale of thousands of user-supplied documents. These processing steps are deployed on a dynamic virtual cluster deployed on XSEDE's Jetstream academic cloud computing resource and are accessed through a Web interface. The science gateway uses Apache Airavata middleware to manage the interactions between the Web interface and the virtual clusters. The gateway leverages the Science Gateway Platform as a service (SciGaP) infrastructure at Indiana University, which provides user authentication, authorization, and identity management as well as access to the Distant Reader tools. The Distant Reader is designed to assist in the process of using & understanding corpora -- reading.},
 bibtype = {inProceedings},
 author = {Morgan, Eric Lease and Abeysinghe, Eroma and Pamidighantam, Sudhkar and Coulter, Eric and Marru, Suresh and Pierce, Marlon},
 booktitle = {Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning) - PEARC '19}
}

The Distant Reader science gateway can be used to automatically create and analyze text corpora at a scale of thousands of user-supplied documents. These processing steps are deployed on a dynamic virtual cluster deployed on XSEDE's Jetstream academic cloud computing resource and are accessed through a Web interface. The science gateway uses Apache Airavata middleware to manage the interactions between the Web interface and the virtual clusters. The gateway leverages the Science Gateway Platform as a service (SciGaP) infrastructure at Indiana University, which provides user authentication, authorization, and identity management as well as access to the Distant Reader tools. The Distant Reader is designed to assist in the process of using & understanding corpora -- reading.

@inProceedings{
 title = {How the Science Gateways Community Institute Supports Those Who Are Creating Websites to Access Shared Resources},
 type = {inProceedings},
 year = {2019},
 identifiers = {[object Object]},
 pages = {1-4},
 websites = {http://dl.acm.org/citation.cfm?doid=3332186.3333256},
 publisher = {ACM Press},
 city = {New York, New York, USA},
 id = {5ea41de6-b05a-3a41-b8a6-6b45c1bb2744},
 created = {2019-08-19T14:51:27.240Z},
 accessed = {2019-08-19},
 file_attached = {true},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 group_id = {0e433c5b-85c4-32aa-851c-c145aac9f80f},
 last_modified = {2019-09-12T18:48:09.005Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The Science Gateways Community Institute (SGCI) serves the gateway community with free, NSF-funded resources, services, experts, and ideas. Our community shares expertise, technologies, and best practices for creating and sustaining gateways. Gateways offer Web-based access to shared resources, including data, software, computing services, instruments, and educational materials. Gateways are also known by other names, including portals, virtual research environments or virtual labs, eScience, and research cyberinfrastructure.},
 bibtype = {inProceedings},
 author = {Lawrence, Katherine A. and Mullinix, Nayiri and Dahan, Maytal and Hayden, Linda and Pierce, Marlon and Wilkins-Diehr, Nancy and Zentner, Michael},
 booktitle = {Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning) - PEARC '19}
}

The Science Gateways Community Institute (SGCI) serves the gateway community with free, NSF-funded resources, services, experts, and ideas. Our community shares expertise, technologies, and best practices for creating and sustaining gateways. Gateways offer Web-based access to shared resources, including data, software, computing services, instruments, and educational materials. Gateways are also known by other names, including portals, virtual research environments or virtual labs, eScience, and research cyberinfrastructure.

@article{
 title = {Community Organizations: Changing the Culture in Which Research Software Is Developed and Sustained},
 type = {article},
 year = {2019},
 identifiers = {[object Object]},
 keywords = {research software,scientific software,software community culture,software ecosystems,software productivity,software sustainability},
 pages = {8-24},
 volume = {21},
 websites = {https://ieeexplore.ieee.org/document/8565942/},
 month = {3},
 publisher = {IEEE Computer Society},
 day = {1},
 id = {71823032-4391-33bf-ae13-ed8e7c40569f},
 created = {2019-08-19T15:22:10.293Z},
 accessed = {2019-08-19},
 file_attached = {true},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 group_id = {0e433c5b-85c4-32aa-851c-c145aac9f80f},
 last_modified = {2019-09-12T18:48:08.636Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Software is the key crosscutting technology that enables advances in mathematics, computer science, and domain-specific science and engineering to achieve robust simulations and analysis for science, engineering, and other research fields. However, software itself has not traditionally received focused attention from research communities; rather, software has evolved organically and inconsistently, with its development largely as by-products of other initiatives. Moreover, challenges in scientific software are expanding due to disruptive changes in computer hardware, increasing scale and complexity of data, and demands for more complex simulations involving multiphysics, multiscale modeling and outer-loop analysis. In recent years, community members have established a range of grass-roots organizations and projects to address these growing technical and social challenges in software productivity, quality, reproducibility, and sustainability. This article provides an overview of such groups and discusses opportunities to leverage their synergistic activities while nurturing work toward emerging software ecosystems.},
 bibtype = {article},
 author = {Katz, Daniel S. and McInnes, Lois Curfman and Bernholdt, David E. and Mayes, Abigail Cabunoc and Hong, Neil P. Chue and Duckles, Jonah and Gesing, Sandra and Heroux, Michael A. and Hettrick, Simon and Jimenez, Rafael C. and Pierce, Marlon and Weaver, Belinda and Wilkins-Diehr, Nancy},
 journal = {Computing in Science & Engineering},
 number = {2}
}

Software is the key crosscutting technology that enables advances in mathematics, computer science, and domain-specific science and engineering to achieve robust simulations and analysis for science, engineering, and other research fields. However, software itself has not traditionally received focused attention from research communities; rather, software has evolved organically and inconsistently, with its development largely as by-products of other initiatives. Moreover, challenges in scientific software are expanding due to disruptive changes in computer hardware, increasing scale and complexity of data, and demands for more complex simulations involving multiphysics, multiscale modeling and outer-loop analysis. In recent years, community members have established a range of grass-roots organizations and projects to address these growing technical and social challenges in software productivity, quality, reproducibility, and sustainability. This article provides an overview of such groups and discusses opportunities to leverage their synergistic activities while nurturing work toward emerging software ecosystems.

@inProceedings{
 title = {Research Computing at a Business University},
 type = {inProceedings},
 year = {2019},
 identifiers = {[object Object]},
 pages = {1-5},
 publisher = {Association for Computing Machinery (ACM)},
 id = {17908b2c-16f9-3745-a995-1d9d03c48950},
 created = {2019-08-19T16:50:48.631Z},
 accessed = {2019-08-19},
 file_attached = {true},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 group_id = {0e433c5b-85c4-32aa-851c-c145aac9f80f},
 last_modified = {2019-08-27T14:14:29.028Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Research Computing demands are exploding beyond traditional disciplines due to the proliferation of data in all walks of life. At Bentley University ("Bentley"), a business university in the Boston area, this expansion has been most readily seen in our Accounting, Economics, Mathematics, and Natural Sciences departments. The result has been a small effort to build a research computing capability at this small New England university. This poster will serve as an overview of the steps taken to build such an effort at a business university, the revelations we have had along the way, and our plans for the future.},
 bibtype = {inProceedings},
 author = {Wells, Jason and Coulter, J. Eric},
 booktitle = {Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning) - PEARC '19}
}

Research Computing demands are exploding beyond traditional disciplines due to the proliferation of data in all walks of life. At Bentley University ("Bentley"), a business university in the Boston area, this expansion has been most readily seen in our Accounting, Economics, Mathematics, and Natural Sciences departments. The result has been a small effort to build a research computing capability at this small New England university. This poster will serve as an overview of the steps taken to build such an effort at a business university, the revelations we have had along the way, and our plans for the future.

@inProceedings{
 title = {Beyond Campus Bridging},
 type = {inProceedings},
 year = {2019},
 identifiers = {[object Object]},
 pages = {1-4},
 websites = {http://dl.acm.org/citation.cfm?doid=3332186.3333151},
 publisher = {ACM Press},
 city = {New York, New York, USA},
 id = {c9b96599-b872-3426-b97d-47210e617484},
 created = {2019-08-19T16:51:48.136Z},
 accessed = {2019-08-19},
 file_attached = {true},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 group_id = {0e433c5b-85c4-32aa-851c-c145aac9f80f},
 last_modified = {2019-09-24T19:53:51.182Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {An abstract is not available},
 bibtype = {inProceedings},
 author = {Coulter, J. Eric and Knepper, Rich and Reynolds, Resa and Sprouse, Jodie and Bird, Stephen},
 booktitle = {Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning) - PEARC '19}
}

An abstract is not available

@article{
 title = {Science gateways: Sustainability via on-campus teams},
 type = {article},
 year = {2019},
 identifiers = {[object Object]},
 keywords = {On-campus groups,Science gateways,Science gateways community institute,Sustainability},
 pages = {97-102},
 volume = {94},
 websites = {https://linkinghub.elsevier.com/retrieve/pii/S0167739X18315395},
 month = {5},
 publisher = {Elsevier B.V.},
 day = {1},
 id = {324294eb-9887-3070-99e2-86744731308e},
 created = {2019-08-19T17:09:24.076Z},
 accessed = {2019-08-19},
 file_attached = {true},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 group_id = {0e433c5b-85c4-32aa-851c-c145aac9f80f},
 last_modified = {2019-09-12T17:56:21.544Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The challenges for creators of specific science gateways are manifold, and the expertise needed for well-designed science gateways is very diverse. The sustainability of science gateways is crucial to serve communities effectively, efficiently and reliably. One measure to achieve greater sustainability of science gateways is establishing on-campus teams. Researchers are served more efficiently since the support by experienced developers reduces individual project investments, and a team can bring the diversity of required expertise for a well-designed science gateway. This paper goes into detail about the challenges and the benefits of on-campus groups and of sharing resources across a campus. We provide four successful cases, describe the services of the Science Gateways Community Institute (SGCI) to support the process in building such groups, and recommend strategies for using free campus resources.},
 bibtype = {article},
 author = {Gesing, Sandra and Lawrence, Katherine and Dahan, Maytal and Pierce, Marlon E. and Wilkins-Diehr, Nancy and Zentner, Michael},
 journal = {Future Generation Computer Systems}
}

The challenges for creators of specific science gateways are manifold, and the expertise needed for well-designed science gateways is very diverse. The sustainability of science gateways is crucial to serve communities effectively, efficiently and reliably. One measure to achieve greater sustainability of science gateways is establishing on-campus teams. Researchers are served more efficiently since the support by experienced developers reduces individual project investments, and a team can bring the diversity of required expertise for a well-designed science gateway. This paper goes into detail about the challenges and the benefits of on-campus groups and of sharing resources across a campus. We provide four successful cases, describe the services of the Science Gateways Community Institute (SGCI) to support the process in building such groups, and recommend strategies for using free campus resources.

@inProceedings{
 title = {Towards a science gateway reference architecture},
 type = {inProceedings},
 year = {2019},
 keywords = {Cyberinfrastructure,Science gateways},
 volume = {2357},
 publisher = {CEUR-WS},
 id = {25e4bc2e-62d7-3af7-937e-d917e442a5b8},
 created = {2019-08-19T17:14:13.768Z},
 accessed = {2019-08-19},
 file_attached = {false},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 group_id = {0e433c5b-85c4-32aa-851c-c145aac9f80f},
 last_modified = {2019-08-27T14:14:29.186Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Science gateways have been developed over the last twenty years and have grown into a large community of practice, as evidenced by international workshops and conferences. Because of the diversity of approaches to creating science gateways and the always changing landscape of technologies, the community lacks a common definition for the term " science gateway " itself and common terminology for describing the common components of a gateway architecture. Instead, a wide range of definitions and understandings exist and are used in different communities; this is evident, for example, in discussions whether science gateways are the same as virtual research environments. This paper attempts to address these issues by focusing on how science gateways support scientific research and considering the consequences on cyberinfrastructure.},
 bibtype = {inProceedings},
 author = {Pierce, Marlon E. and Miller, Mark A. and Brookes, Emre H. and Wong, Mona and Afgan, Enis and Liu, Yan and Gesing, Sandra and Dahan, Maytal and Walker, Tony and Marru, Suresh},
 booktitle = {CEUR Workshop Proceedings}
}

Science gateways have been developed over the last twenty years and have grown into a large community of practice, as evidenced by international workshops and conferences. Because of the diversity of approaches to creating science gateways and the always changing landscape of technologies, the community lacks a common definition for the term " science gateway " itself and common terminology for describing the common components of a gateway architecture. Instead, a wide range of definitions and understandings exist and are used in different communities; this is evident, for example, in discussions whether science gateways are the same as virtual research environments. This paper attempts to address these issues by focusing on how science gateways support scientific research and considering the consequences on cyberinfrastructure.

@inProceedings{
 title = {Experiences from scaling scale Science Gateway operations},
 type = {inProceedings},
 year = {2019},
 identifiers = {[object Object]},
 pages = {1-4},
 websites = {http://dl.acm.org/citation.cfm?doid=3332186.3333159},
 publisher = {ACM Press},
 city = {New York, New York, USA},
 id = {940bfc86-7f4a-3031-8906-6400609541f0},
 created = {2019-09-12T14:52:51.712Z},
 accessed = {2019-09-12},
 file_attached = {true},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 group_id = {0e433c5b-85c4-32aa-851c-c145aac9f80f},
 last_modified = {2019-09-12T15:02:48.301Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Science gateways are distributed computing systems that provide science-centric, end-user environments that simplify and expand the use of scientific software and data on diverse scientific software on backend resources. In this poster we describe the experiences of using a common software platform to host "Software as a Service" Science Gateways.},
 bibtype = {inProceedings},
 author = {Marru, Suresh and Piece, Marlon and Abeysinghe, Eroma and Pamidighantam, Sudhakar and Christie, Marcus and Wannipurage, Dimuthu},
 booktitle = {Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning) - PEARC '19}
}

Science gateways are distributed computing systems that provide science-centric, end-user environments that simplify and expand the use of scientific software and data on diverse scientific software on backend resources. In this poster we describe the experiences of using a common software platform to host "Software as a Service" Science Gateways.

@inProceedings{
 title = {Implementing a Flexible, Fault Tolerant Job Management System for Science Gateways},
 type = {inProceedings},
 year = {2019},
 identifiers = {[object Object]},
 pages = {1-8},
 websites = {http://dl.acm.org/citation.cfm?doid=3332186.3332233},
 publisher = {ACM Press},
 city = {New York, New York, USA},
 id = {d7960396-ea86-374e-8e21-19aff8754c14},
 created = {2019-09-12T15:02:36.044Z},
 accessed = {2019-09-12},
 file_attached = {true},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 group_id = {0e433c5b-85c4-32aa-851c-c145aac9f80f},
 last_modified = {2019-09-12T18:48:08.801Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {This paper summarizes our experiences evaluating and deploying a new task execution management system within the open source Apache Airavata framework for science gateways. We base our choices on our operational requirements and experiences running Airavata software as a multi-tenanted production service for multiple gateway clients. Our considerations include integrating semi-independent components, making major upgrades to those components while retaining the system's overall functionality, and choosing between integrating third party and in-house developed components. While we focus on Apache Airavata as the platform for evaluation, our results should be of general interest. After considering the options of extensions to our previous, in-house job management system using Apache Kafka or replacing it with Kubernetes, we ultimately chose Apache Helix, primarily for its ability to execute multiple tasks coupled into directed acyclic graphs. We have integrated this approach into Apache Airavata and have tested extensively over several months with many thousands of jobs, both from our internal throughput testing and operational tests with early adopter science gateway clients. The new system has proven to be at least as reliable as the previous system with the advantages that we now have simplified maintenance, do not need to support an in-house system that required extensive developer training to modify, and can support more sophisticated job execution scenarios.},
 bibtype = {inProceedings},
 author = {Wannipurage, Dimuthu and Marru, Suresh and Piece, Marlon and Abeysinghe, Eroma and Pamidighantam, Sudhakar and Christie, Marcus and Shenoy, Gourav and Dhamnaskar, Ajinkya and Jayathilaka, Lahiru},
 booktitle = {Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning) - PEARC '19}
}

This paper summarizes our experiences evaluating and deploying a new task execution management system within the open source Apache Airavata framework for science gateways. We base our choices on our operational requirements and experiences running Airavata software as a multi-tenanted production service for multiple gateway clients. Our considerations include integrating semi-independent components, making major upgrades to those components while retaining the system's overall functionality, and choosing between integrating third party and in-house developed components. While we focus on Apache Airavata as the platform for evaluation, our results should be of general interest. After considering the options of extensions to our previous, in-house job management system using Apache Kafka or replacing it with Kubernetes, we ultimately chose Apache Helix, primarily for its ability to execute multiple tasks coupled into directed acyclic graphs. We have integrated this approach into Apache Airavata and have tested extensively over several months with many thousands of jobs, both from our internal throughput testing and operational tests with early adopter science gateway clients. The new system has proven to be at least as reliable as the previous system with the advantages that we now have simplified maintenance, do not need to support an in-house system that required extensive developer training to modify, and can support more sophisticated job execution scenarios.

@inProceedings{
 title = {Towards Run Time Estimation of the Gaussian Chemistry Code for SEAGrid Science Gateway},
 type = {inProceedings},
 year = {2019},
 identifiers = {[object Object]},
 pages = {1-8},
 websites = {http://dl.acm.org/citation.cfm?doid=3332186.3338101},
 publisher = {ACM Press},
 city = {New York, New York, USA},
 id = {3c9ce98b-b753-3c39-a498-c48fb5d00a72},
 created = {2019-09-12T17:32:23.055Z},
 accessed = {2019-09-12},
 file_attached = {true},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 group_id = {0e433c5b-85c4-32aa-851c-c145aac9f80f},
 last_modified = {2019-09-19T15:37:54.626Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Accurate estimation of the run time of computational codes has a number of significant advantages for scientific computing. It is required information for optimal resource allocation, improving turnaround times and utilization of science gateways. Furthermore, it allows users to better plan and schedule their research, streamlining workflows and improving the overall productivity of cyberinfrastructure. Predicting run time is challenging, however. The inputs to scientific codes can be complex and high dimensional. Their relationship to the run time may be highly non-linear, and, in the most general case is completely arbitrary and thus unpredictable (i.e., simply a random mapping from inputs to run time). Most codes are not so arbitrary, however, and there has been significant prior research on predicting the run time of applications and workloads. Such predictions are generally application-specific, however. In this paper, we focus on the Gaussian computational chemistry code. We characterize a data set of runs from the SEAGrid science gateway with a number of different studies. We also explore a number of different potential regression methods and present promising future directions.},
 bibtype = {inProceedings},
 author = {Beltre, Angel and Zaman, Shehtab and Chiu, Kenneth and Pamidighantam, Sudhakar and Qiao, Xingye and Govindaraju, Madhusudhan},
 booktitle = {Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning) - PEARC '19}
}

Accurate estimation of the run time of computational codes has a number of significant advantages for scientific computing. It is required information for optimal resource allocation, improving turnaround times and utilization of science gateways. Furthermore, it allows users to better plan and schedule their research, streamlining workflows and improving the overall productivity of cyberinfrastructure. Predicting run time is challenging, however. The inputs to scientific codes can be complex and high dimensional. Their relationship to the run time may be highly non-linear, and, in the most general case is completely arbitrary and thus unpredictable (i.e., simply a random mapping from inputs to run time). Most codes are not so arbitrary, however, and there has been significant prior research on predicting the run time of applications and workloads. Such predictions are generally application-specific, however. In this paper, we focus on the Gaussian computational chemistry code. We characterize a data set of runs from the SEAGrid science gateway with a number of different studies. We also explore a number of different potential regression methods and present promising future directions.

@inProceedings{
 title = {Virtual Clusters in the Jetstream Cloud},
 type = {inProceedings},
 year = {2019},
 identifiers = {[object Object]},
 pages = {1-6},
 websites = {http://dl.acm.org/citation.cfm?doid=3355738.3355752},
 publisher = {ACM Press},
 city = {New York, New York, USA},
 id = {54b66bc6-cf93-37d4-80f4-d1cf6ef1458f},
 created = {2019-09-24T19:28:18.895Z},
 accessed = {2019-09-24},
 file_attached = {true},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 group_id = {0e433c5b-85c4-32aa-851c-c145aac9f80f},
 last_modified = {2019-09-24T19:53:51.173Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {We discuss our work providing resources for batch computing via the Jetstream cloud, in the form of SLURM clusters. While these are mainly used by science gateways, there have been a few used in the more traditional commandline manner. The flexible nature of these has also lent itself well to educational work, and has provided the basis for a very successful series of tutorials and workshops. This paper discusses the technical evolution of the Virtual Cluster product, and gives an overview of the science enabled. We discuss the challenges in supporting an ecosystem of these virtual clusters, and in supporting research on cloud resources in general.},
 bibtype = {inProceedings},
 author = {Coulter, J. Eric and Abeysinghe, Eroma and Pamidighantam, Sudhakar and Pierce, Marlon},
 booktitle = {Proceedings of the Humans in the Loop: Enabling and Facilitating Research on Cloud Computing - HARC '19}
}

We discuss our work providing resources for batch computing via the Jetstream cloud, in the form of SLURM clusters. While these are mainly used by science gateways, there have been a few used in the more traditional commandline manner. The flexible nature of these has also lent itself well to educational work, and has provided the basis for a very successful series of tutorials and workshops. This paper discusses the technical evolution of the Virtual Cluster product, and gives an overview of the science enabled. We discuss the challenges in supporting an ecosystem of these virtual clusters, and in supporting research on cloud resources in general.

@article{
 title = {Programmable Education Infrastructure: Cloud resources as HPC Education Environments},
 type = {article},
 year = {2019},
 identifiers = {[object Object]},
 pages = {107-107},
 volume = {10},
 websites = {http://www.jocse.org/articles/10/1/18/},
 month = {1},
 publisher = {The Shodor Education Foundation, Inc.},
 id = {a110bf64-b3ce-3998-8535-e35d2badac31},
 created = {2019-09-24T19:55:27.980Z},
 accessed = {2019-09-24},
 file_attached = {false},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 group_id = {0e433c5b-85c4-32aa-851c-c145aac9f80f},
 last_modified = {2019-09-24T19:55:27.980Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Cloud computing is growing area for educating students and per- forming meaningful scientific research. The challenge for many educators and researchers is knowing how to use some of the unique aspects of computing in the cloud. One key feature is true elastic computing - resources on demand. The elasticity and programmability of cloud resources make them an excellent tool for educators who require access to a wide range of computing environments. In the field of HPC education, such environments are an absolute necessity, and getting access to them can create a large burden on the educators above and beyond designing content. While cloud resources won't replace traditional HPC environments for large research projects, they are an excellent option for providing both user and administrator education on HPC environments. The highly configurable nature of cloud environments allows educators to tailor the educational resource to the needs of their attendees, and provide a wide range of hands-on experiences. In this demo, we'll show how the Jetstream cloud environment can be used to provide training for both new HPC administrators and users, by showing a ground-up build of a simple HPC system. While this approach uses the Jetstream cloud, it is generalizable across any cloud provider. We will show how this allows an educator to tackle everything from basic command-line concepts and scheduler use to advanced cluster-management concepts such