25 papers · ranked by Valyu relevance
Jeannette M. Wing
Computational thinking will influence everyone in every field of endeavour. This vision poses a new educational challenge for our society, especially for our children. In thinking about computing, we need to be attuned to the three drivers of our field: science, technology and society. Accelerating technological…
Jeremy Li, Alex Rubinsteyn, Sergey Feldman, Timothy O’Donnell + 18 more
Scientific computing has become a central component of modern scientific discovery. Yet many computational tools are developed by small, specialized teams under incentives that encourage the release of rapidly prototyped tooling without commensurate attention to engineering concerns, including performance and…
Matthew G. Knepley
Scientific computation is a discipline that combines numerical analysis, physical understanding, algorithm development, and structured programming. Several yottacycles per year on the world's largest computers are spent simulating problems as diverse as weather prediction, the properties of material composites, the…
Marcelo Ponce, E. J. Spence, Daniel Gruner, Ramses van Zon
We present an overview of current academic curricula for Scientific Computing, High-Performance Computing and Data Science. After a survey of current academic and non-academic programs across the globe, we focus on Canadian programs and specifically on the education program of the SciNet HPC Consortium, using its…
Pablo García‐Risueño, Pablo Ibáñez
The increase of existing computational capabilities has made simulation emerge as a third discipline of Science, lying midway between experimental and purely theoretical branches [1, 2]. Simulation enables the evaluation of quantities which otherwise would not be accessible, helps to improve experiments and provides…
Vasant Honavar, Mark D. Hill, Katherine Yelick
The emergence of "big data" offers unprecedented opportunities for not only accelerating scientific advances but also enabling new modes of discovery. Scientific progress in many disciplines is increasingly enabled by our ability to examine natural phenomena through the computational lens, i.e., using algorithmic or…
Chaoming Wang, Sichao He, Shouwei Luo, Yuxiang Huan + 1 more
Artificial intelligence (AI) is revolutionizing scientific research across various disciplines. The foundation of scientific research lies in rigorous scientific computing based on standardized physical units. However, current mainstream high-performance numerical computing libraries for AI generally lack native…
Ramses van Zon, Marcelo Ponce, E. J. Spence, Daniel Gruner
We analyze the changes in the training and educational efforts of the SciNet HPC Consortium, a Canadian academic High Performance Computing center, in the areas of Scientific Computing and High-Performance Computing, over the last six years. Initially, SciNet offered isolated training events on how to use HPC systems…
David S. Cerutti, Rafal Wiewiora, Simon Boothroyd, Woody Sherman
The Structure and TOpology Replica Molecular Mechanics (STORMM) code is a next-generation molecular simulation engine and associated libraries optimized for performance on fast, multicore central processor units (CPUs) and graphics processing units (GPUs) with independent memory and tens of thousands of threads. STORMM…
Konrad Hinsen
Computational techniques have revolutionized many aspects of scientific research over the last few decades. Experimentalists use computation for data analysis, processing ever bigger data sets. Theoreticians compute predictions from ever more complex models. However, traditional articles do not permit the publication…
Konrad Hinsen, Daniel Katz
Most of today’s scientific research relies on computers and software for processing scientific information. Examples of such computer-aided research are the analysis of experimental data or the simulation of phenomena based on theoretical models. With the rapid increase of computational power, scientific software has…
Yizi Shang, Ling Shang, Chuanchang Gao, Guiming Lu + 2 more
'Dongdong Jia'] This paper is to make further research on facilitating the large-scale scientific computing on the grid and the desktop grid platform. The related issues include the programming method, the overhead of the high-level program interface based middleware, and the data anticipate migration. The block based…
Authors not listed
The era of exascale computing presents both exciting opportunities and unique challenges for quantum mechanical simulations. While the transition from petaflops to exascale computing has been marked by a steady increase in computational power, the shift towards heterogeneous architectures, particularly the dominant…
Oliver Lee, Malte Gather, Eli Zysman-Colman
We describe a new tool for the efficient management of computational chemistry. Digichem is a program that automates and simplifies nearly the entire computational pipeline, including large-scale batch submission of calculations, analysis and results parsing, the generation of 3D density plots and 2D graphs of…
Authors not listed
Agentic artificial intelligence (AI) is poised to redefine how science is conducted, automating not just data analysis but the entire research lifecycle, from hypothesis generation to validation. Yet most current AI agents remain domain-bound, tailored to specific applications such as materials synthesis or quantum…
Amelie Chi Zhou, Bingsheng He, Shadi Ibrahim
—Cloud computing has recently evolved as a popular computing infrastructure for many applications. Scientific computing, which was mainly hosted in private clusters and grids, has started to migrate development and deployment to the public cloud environment. eScience as a service becomes an emerging and promising…
Tessa Durham Brooks, Raychelle Burks, Erin Doyle, Mark Meysenburg + 1 more
In many areas of science, the ability to use computers to process, analyze, and visualize large data sets has become essential. The mismatch between the ability to generate large data sets and the computing skill to analyze them is arguably the most striking within the life sciences. The Digital Image and Vision…
Alan Aspuru-Guzik, Roland Lindh, Markus Reiher
To date, the program for the development of methods and models for atomistic and continuum simulation directed toward chemicals and materials has reached an incredible degree of sophistication and maturity. Currently, one can witness an increasingly rapid emergence of advances in computing, artificial intelligence, and…
Madushanka Manathunga, Hasan Metin Aktulga, Andreas W. Goetz, Kenneth M. Merz + 1 more
We have ported and optimized the GPU accelerated QUICK and AMBER based ab initio QM/MM implementation on AMD GPUs. This encompasses the entire Fock matrix build and force calculation in QUICK including one-electron integrals, two-electron repulsion integrals, exchange-correlation quadrature, and linear algebra…
Tarek Sherif, Pierre Rioux, Marc-Etienne Rousseau, Nicolas Kassis + 5 more
'Natacha Beck' 'Reza Adalat' 'Samir Das' 'Tristan Glatard' 'Alan C. Evans'] The Canadian Brain Imaging Research Platform (CBRAIN) is a web-based collaborative research platform developed in response to the challenges raised by data-heavy, compute-intensive neuroimaging research. CBRAIN offers transparent access to…
Brian S. Cole, Jason H. Moore, Francis Ouellette
Cloud computing has revolutionized the development and operations of hardware and software across diverse technological arenas, yet academic biomedical research has lagged behind despite the numerous and weighty advantages that cloud computing offers. Biomedical researchers who embrace cloud computing can reap rewards…
Hugo Hiden, Simon Woodman, Paul Watson, Jacek Cala
This paper describes the e-Science Central (e-SC) cloud data processing system and its application to a number of e-Science projects. e-SC provides both software as a service (SaaS) and platform as a service for scientific data management, analysis and collaboration. It is a portable system and can be deployed on both…
Authors not listed
Imagine a computer capable of solving currently unsolvable problems. Quantum computing leverages the principles of quantum mechanics to tackle complex challenges that would take classical computers centuries to complete. In this Commentary, we explore the current state of quantum computing development and how it will…
Andrew McCluskey, Miguel Rivera, Antonia Mey
The role of computing in the chemical sciences is changing. Previously the domain of the theoretical or computational chemist, advanced digital skills, including data analysis and simulation, are becoming extremely relevant to all. Here, we discuss the importance of integrating computing and digital skills into an…
David Mayer, Seth Russell, Melissa P. Wilson, Michael G. Kahn + 1 more
One of the challenges of teaching applied data science courses is managing individual students’ local computing environment. This is especially challenging when teaching massively open online courses (MOOCs) where students come from across the globe and have a variety of access to and types of computing systems. There…