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Enhancing Scientific Research with FAIR Digital Objects in the National Science Data Fabric Comput. Sci. Eng. (IF 2.1) Pub Date : 2024-04-18 Michela Taufer, Heberth Martinez, Jakob Luettgau, Lauren Whitnah, Giorgio Scorzelli, Pania Newell, Aashish Panta, Peer-Timo Bremer, Douglas Fils, Christine R. Kirkpatrick, Valerio Pascucci
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Performance on HPC Platforms Is Possible Without C++ Comput. Sci. Eng. (IF 2.1) Pub Date : 2024-04-18 Anshu Dubey, Tal Ben-Nun, Bradford L. Chamberlain, Bronis R. de Supinski, Damian Rouson
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Get Published in the New IEEE Transactions on Privacy Comput. Sci. Eng. (IF 2.1) Pub Date : 2024-04-18
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Accelerating Scientific Discovery With AI-Aided Automation Comput. Sci. Eng. (IF 2.1) Pub Date : 2024-04-18 Tapio Schneider, Ilkay Altintas, Daniel Atkins
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Tensor Computations—Part I Comput. Sci. Eng. (IF 2.1) Pub Date : 2024-04-18 Adrian Feiguin, Stefanos Kourtis
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A cast of thousands: How the IDEAS Productivity project has advanced software productivity and sustainability Comput. Sci. Eng. (IF 2.1) Pub Date : 2024-04-16 Lois Curfman McInnes, Michael Heroux, David E. Bernholdt, Anshu Dubey, Elsa Gonsiorowski, Rinku Gupta, Osni Marques, J. David Moulton, Hai Ah Nam, Boyana Norris, Elaine M. Raybourn, Jim Willenbring, Ann Almgren, Ross Bartlett, Kita Cranfill, Stephen Fickas, Don Frederick, William Godoy, Patricia Grubel, Rebecca Hartman-Baker, Axel Huebl, Rose Lynch, Addi Malviya Thakur, Reed Milewicz, Mark C. Miller
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Then and Now: Improving Software Portability, Productivity, and 100× Performance Comput. Sci. Eng. (IF 2.1) Pub Date : 2024-04-10 Hartwig Anzt, Axel Huebl, Xiaoye S Li
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Scalable Delivery of Scalable Libraries and Tools: How ECP Delivered a Software Ecosystem for Exascale and Beyond Comput. Sci. Eng. (IF 2.1) Pub Date : 2024-04-05 Michael A. Heroux
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Co-design for Particle Applications at Exascale Comput. Sci. Eng. (IF 2.1) Pub Date : 2024-04-03 Samuel Temple Reeve, Jean-Luc Fattebert, Stephen DeWitt, David Joy, Pablo Seleson, Stuart Slattery, Aaron Scheinberg, Rene Halver, Christoph Junghans, Christian F. A. Negre, Michael E. Wall, Yu Zhang, Anders M. Niklasson, Danny Perez, Susan M. Mniszewski, James Belak
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XaaS: Acceleration as a Service to Enable Productive High-Performance Cloud Computing Comput. Sci. Eng. (IF 2.1) Pub Date : 2024-04-02 Torsten Hoefler, Marcin Copik, Pete Beckman, Andrew Jones, Ian Foster, Manish Parashar, Daniel Reed, Matthias Troyer, Thomas Schulthess, Dan Ernst, Jack Dongarra
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A Differentiated Diversity: Demographic Patterns and Contextual Delineations in U.S. Computing Comput. Sci. Eng. (IF 2.1) Pub Date : 2024-03-29 Connie L. McNeely, Lisa M. Frehill
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Secure Federated Learning Across Heterogeneous Cloud and High-Performance Computing Resources - A Case Study on Federated Fine-tuning of LLaMA 2 Comput. Sci. Eng. (IF 2.1) Pub Date : 2024-03-29 Zilinghan Li, Shilan He, Pranshu Chaturvedi, Volodymyr Kindratenko, Eliu A Huerta, Kibaek Kim, Ravi Madduri
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Reproducing the Results for NICER Observation of PSR J0030+0451 Comput. Sci. Eng. (IF 2.1) Pub Date : 2024-03-27 C. Afle, P. R. Miles, S. Caíno-Lores, C. D. Capano, I. Tews, K. Vahi, E. Deelman, M. Taufer, D. A. Brown
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The Intelligence Advanced Research Projects Activity Advanced Graph Intelligent Logical Computing Environment Program: Reinventing Computing Comput. Sci. Eng. (IF 2.1) Pub Date : 2024-02-15 William J. Harrod
New data-centric architectures optimized for knowledge discovery and analytics are urgently required. This article describes the Intelligence Advanced Research Projects Activity’s Advanced Graph Intelligent Logical Computing Environment program, the first step toward catalyzing a computing revolution by pioneering new hardware and software co-designs tailored for data handling and movement. The goal
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Mochi: A Case Study in Translational Computer Science for High-Performance Computing Data Management Comput. Sci. Eng. (IF 2.1) Pub Date : 2024-02-15 Philip Carns, Matthieu Dorier, Rob Latham, Robert B. Ross, Shane Snyder, Jerome Soumagne
High-performance computing (HPC) has become an indispensable tool for solving diverse problems in science and engineering. Harnessing the power of HPC is not just a matter of efficient computation, however; it also calls for the efficient management of vast quantities of scientific data. This presents daunting challenges: rapidly evolving storage technology has motivated a shift toward increasingly
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Challenges and Techniques for Reproducible Simulations Comput. Sci. Eng. (IF 2.1) Pub Date : 2024-02-15 Curran D. Muhlberger
Too often, reproducibility is unnecessarily sacrificed in new simulation codes. We explore some ways in which this happens and provide recommendations for reclaiming it. Experience shows that robust bitwise reproducibility on a fixed runtime platform is a desirable and achievable target. The variety of threats considered suggests that maintaining a reproducible simulator to this degree requires vigilance
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Discrete Wildfire Simulation Case Study Comput. Sci. Eng. (IF 2.1) Pub Date : 2024-02-15 Micah D. Schuster
Wildfire activity around the world has been increasing for the past several decades. This has led to increased frequency of wildfires and longer fire seasons. When a fire is detected, one of the most important considerations is where to allocate limited firefighting resources to best contain the fire and protect infrastructure and urban areas. This is where robust, high-resolution fire simulations
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Creating Continuous Integration Infrastructure for Software Development on DOE HPC Systems Comput. Sci. Eng. (IF 2.1) Pub Date : 2024-02-07 Ryan Adamson, Paul Bryant, Dave Montoya, Jeff Neel, Erik Palmer, Ray Powell, Ryan Prout, Peter Upton
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An Intuitive Tutorial to Gaussian Process Regression Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-12-14 Jie Wang
This tutorial aims to provide an intuitive introduction to Gaussian process regression (GPR). GPR models have been widely used in machine learning applications due to their representation flexibility and inherent capability to quantify uncertainty over predictions. The tutorial starts with explaining the basic concepts that a Gaussian process is built on, including multivariate normal distribution
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Adopting Software Engineering Concepts in Scientific Research: Insights from Physicists and Mathematicians Turned Consultants Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-11-06 Marc Thomas Schönborn
Physicists and mathematicians spend a fair amount of their research time developing software, as most modern calculations cannot be solved analytically and require numerical solutions. Despite this situation, researchers in these areas tend to place little importance on integrating formal software engineering concepts (SECs) into their projects. To investigate the potential benefits of SECs in scientific
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Computational Modeling of Ice Sheets and Glaciers Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-10-30 Irina Tezaur, Josefin Ahlkrona, Matthew Hoffman, Mauro Perego
The four articles in this special section focus on the development and efficient implementation of numerical, computational, and data driven methods for reliable, next-generation ISMs, toward addressing some of these challenges. These articles span a variety of topics, ranging from mechanics based modeling of hydrofracture and ice calving, to novel, compatible finite-element discretizations, to data-driven
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Earth Virtualization Engines: A Technical Perspective Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-10-30 Torsten Hoefler, Bjorn Stevens, Andreas F. Prein, Johanna Baehr, Thomas Schulthess, Thomas F. Stocker, John Taylor, Daniel Klocke, Pekka Manninen, Piers M. Forster, Tobias Kölling, Nicolas Gruber, Hartwig Anzt, Claudia Frauen, Florian Ziemen, Milan Klöwer, Karthik Kashinath, Christoph Schär, Oliver Fuhrer, Bryan N. Lawrence
Participants of the Berlin Summit on Earth Virtualization Engines (EVEs) discussed ideas and concepts to improve our ability to cope with climate change. EVEs aim to provide interactive and accessible climate simulations and data for a wide range of users. They combine high-resolution physics-based models with machine learning techniques to improve the fidelity, efficiency, and interpretability of
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Managing Software Provenance to Enhance Reproducibility in Computational Research Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-10-30 Akash Dhruv, Anshu Dubey
Scientific processes rely on software as an important tool for data acquisition, analysis, and discovery. Over the years, sustainable software development practices have made progress in being considered as an integral component of research. However, management of computation-based scientific studies is often left to individual researchers who design their computational experiments based on personal
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Simulation for All: The Atomic, Molecular, and Optical Science Gateway Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-10-30 Kathryn R. Hamilton, Klaus Bartschat, Nicolas Douguet, Sudhakar V. Pamidighantam, Barry I. Schneider
The Atomic, Molecular, and Optical Sciences Gateway (AMOSGateway) enables novice and experienced users to utilize state-of-the-art software suites for tackling problems central to atomic, molecular, and optical science. This international collaboration provides a free platform and coordinated approach for computational research, allowing the community to produce new scientific results on an unprecedented
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Six Opportunities for Scientists and Engineers to Learn Programming Using AI Tools Such as ChatGPT Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-10-30 Philip J. Guo
This article demonstrates how scientists and engineers can use modern artificial intelligence (AI) tools such as ChatGPT and GitHub Copilot to learn computer programming skills that are relevant to their jobs. It begins by summarizing common ways that AI tools can already help people learn programming in general and then presents six new opportunities catered to the needs of scientists and engineers:
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Exascale Was Not Inevitable; Neither Is What Comes Next Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-10-30 Erik W. Draeger, Andrew Siegel
The long, steady advance of supercomputing capabilities historically makes it tempting to assume that similar future improvements are inevitable. In fact, the successful path to exascale systems was far from certain, requiring a shift to accelerator-based designs, an associated end-to-end rethinking of traditional computational approaches, and a fundamental change in how scientists collaborate and
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Building on Communities to Further Software Sustainability Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-10-30 Anne Fouilloux, Jean Iaquinta, Alok Kumar Gupta, Hamish Struthers, Oskar Landgren, Prashanth Dwarakanath, Tommi Bergman, Yanchun He
The Nordic e-Infrastructure Collaboration on Earth System Modeling Tools is a small community comprising members with diverse backgrounds, skills, and interests. Largely dependent on temporary staff to develop, operate, and maintain large scientific codes, this community devised strategies to enhance software reusability and sustainability. These strategies include collaborating with other communities
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A Finite-Element-Based Cohesive Zone Model of Water-Filled Surface Crevasse Propagation in Floating Ice Tongues Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-10-04 Yuxiang Gao, Gourab Ghosh, Stephen Jiménez, Ravindra Duddu
We present a finite-element-based cohesive zone model for simulating the nonlinear fracture process driving the propagation of water-filled surface crevasses in floating ice tongues. The fracture process is captured using an interface element whose constitutive behavior is described by a bilinear cohesive law, and the bulk rheology of ice is described by a nonlinear elasto-viscoplastic model. The additional
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A Python Multiprocessing Approach for Fast Geostatistical Simulations of Subglacial Topography Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-09-22 Nathan W. Schoedl, Emma J. MacKie, Michael J. Field, Eric A. Stubbs, Allan Zhang, Matthew Hibbs, Mathieu Gravey
Realistically rough stochastic realizations of subglacial bed topography are crucial for improving our understanding of basal processes and quantifying uncertainty in sea level rise projections with respect to topographic uncertainty. This can be achieved with sequential Gaussian simulation (SGS), which is used to generate multiple nonunique realizations of geological phenomena that sample the uncertainty
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Science Gateways: Accelerating Research and Education—Part II Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-08-25 Patrick Diehl, Rafael Ferreira da Silva
Science gateways are essential for connecting researchers with advanced cyber infrastructure resources. These user-friendly interfaces simplify resource access and utilization, enabling scientists from diverse fields to leverage computational resources, data collections, analytical tools, and remote instruments. By democratizing access and streamlining the complex process, science gateways empower
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The 2023 Society for Industrial and Applied Mathematics Conference on Computational Science and Engineering Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-08-25 Damian Rouson, Konrad Hinsen, Jeffrey Carver, Irina Tezaur, John Shalf, Rio Yokota, Anshu Dubey
This note gives highlights and key takeaways from Computing in Science & Engineering editors who attended the 2023 Society for Industrial and Applied Mathematics Conference on Computational Science and Engineering. The editors discuss themes such as the benefits of returning to in-person conferences, progress in scientific software development and adoption, domain-specific languages, machine learning
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Leverage Biology to Learn Rapidly From Mistakes Without Feeling Like a Failure Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-08-25 Lauren E. Margulieux, James Prather, Masoumeh Rahimi, Gozde Cetin Uzun
Our biology affects how we interact with the world, including how we learn new knowledge and respond to challenges. This article explores the impact of neurochemicals in our brain on learning and explains how to leverage our biology to improve education and problem solving, focusing on computing education. Within this context, the article particularly examines the role of failure while learning. Learning
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Reflecting on the Scalable Adaptive Graphics Environment Team’s 20-Year Translational Research Endeavor in Digital Collaboration Tools Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-08-25 Mahdi Belcaid, Jason Leigh, Ryan Theriot, Nurit Kirshenbaum, Roderick Tabalba, Michael Rogers, Andrew Johnson, Maxine Brown, Luc Renambot, Lance Long, Arthur Nishimoto, Chris North, Jesse Harden
Translational software research bridges the gap between scientific innovations and practical applications, driving impactful societal advancements. However, developing such software is challenging due to interdisciplinary collaboration, technology adoption, and postfunding sustainability. This article presents the experiences and insights of the Scalable Adaptive Graphics Environment (SAGE) team, which
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Data Visualization for Digital Twins Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-08-25 João L. D. Comba, Nicolau O. Santos, Jonathan C. Rivera, Regis K. Romeu, Mara Abel
Visualization techniques are useful in the analysis and insight generation for applications in computing in science and engineering. In this article, we describe the importance of visualization to a digital twin (DT), a virtual representation of a physical object, process or system that can be applied for different tasks, such as data-driven simulation, analysis or monitoring. We illustrate tasks in
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Lattice Gas Cellular Automata Fluid Dynamics: The Model of Frisch, Hasslacher, and Pomeau Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-08-25 Micah D. Schuster
In the November 2020 “Your Homework Assignment” column in Computing in Science & Engineering, the reader was introduced to the cellular automata fluid model of Hardy, Pomeau, and de Pazzis. Although their model captures the microscopic behavior of particles, the square grid restricts the possible interactions such that the model cannot reproduce the Navier–Stokes equations in the continuous limit.
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Compatible Finite Elements for Glacier Modeling Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-08-17 Douglas J. Brinkerhoff
Described in this article is the first application of two mixed finite-element methods to the equations of glacier evolution under different simplifying assumptions, along with a framework for the implicit solution of the coupled velocity-thickness equations. The first method uses Raviart–Thomas elements for velocity and piecewise constants for thickness and is a reframing of a classic staggered-grid
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Science Gateways: Accelerating Research and Education—Part I Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-07-31 Patrick Diehl, Rafael Ferreira da Silva
Most scientific fields have seen a remarkable increase in the use of computational and data-driven research, including physics, chemistry, biology, and astronomy. However, many researchers who lack specialized training in computer science or high-performance computing (HPC) face difficulties in accessing and effectively utilizing these resources. A science gateway serves as a crucial connection point
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Examples of Long-Term Science–Industry Partnerships for Translational Computer Science Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-07-31 Cornelia Travnicek, Veronika Nowak, Rudolf Ramler, Lukas Fischer, Katja Bühler
Although not labeled as such, the three research centers presented in this article have been performing translational computer science (TCS) for more than 20 years. SBA Research, Software Competence Center Hagenberg, and VRVis Zentrum fuer Virtual Reality und Visualisierung, all funded by the Austrian COMET Competence Centers for Excellent Technologies program, each selected one science–industry partnership
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Diversity, Equity, and Inclusion for Computer and Information Science and Engineering Conferences: How Change Happens and Four Things You Can Do Now Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-07-31 Raquell Holmes, Roscoe Giles, Dorian Arnold
The revitalized interest in ensuring that computer and information science and engineering (CISE) is a fair and equitable professional path is one of our grandest opportunities. As professionals who have championed diversity, equity, and inclusion over decades, we are pleased to offer four actions that you, our colleagues, can take to help. In this article, we spotlight the opportunities that exist
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The Nature of Computational Models Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-07-31 Konrad Hinsen
Computational models lie at the heart of computational science, yet few scientists have a clear idea of what a computational model actually is. Is it software? Or an algorithm? How does it relate to mathematical models? What are suitable languages or notations for expressing a computational model in the literature? And will AI make computational models obsolete?
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Numerical Modeling of Neutron Stars Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-07-31 Omair M. Zubairi, Micah D. Schuster
After a star has exhausted all of its fuel by the process of nuclear fusion, it will collapse into a compact object. The three known stellar remnants of the universe are white dwarfs, neutron stars, and black holes. These three objects are characterized by their small size and extremely high densities. To model these compact objects, we must first understand their stellar structure. In this learning
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Statistical Generation of Ocean Forcing With Spatiotemporal Variability for Ice Sheet Models Comput. Sci. Eng. (IF 2.1) Pub Date : 2023-08-01 Shivaprakash Muruganandham, Alexander A. Robel, Matthew J. Hoffman, Stephen F. Price
Melting of ice at the base of floating ice shelves that fringe the Antarctic ice sheet has been identified as a significant source of uncertainty in sea level rise projections. Part of this uncertainty derives from chaotic internal variability of the coupled ocean-atmosphere system. For numerical ice sheet model projections, this uncertainty has not previously been quantified because of the prohibitive