14 papers · ranked by Valyu relevance
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…
Higinio Mora, María Teresa Signes-Pont, David Gil, Magnus Johnsson
The new sensing applications need enhanced computing capabilities to handle the requirements of complex and huge data processing. The Internet of Things (IoT) concept brings processing and communication features to devices. In addition, the Cloud Computing paradigm provides resources and infrastructures for performing…
Behzad D. Karkaria, Neythen J. Treloar, Chris P. Barnes, Alex J. H. Fedorec
A distributed biological system can be defined as a system whose components are located in different subpopulations, which communicate and coordinate their actions through interpopulation messages and interactions. We see that distributed systems are pervasive in nature, performing computation across all scales, from…
Yuliya V Karpievitch, Jonas S Almeida
Background Matlab, a powerful and productive language that allows for rapid prototyping, modeling and simulation, is widely used in computational biology. Modeling and simulation of large biological systems often require more computational resources then are available on a single computer. Existing distributed…
Yunhong Gu, Robert L. Grossman
Cloud computing has demonstrated that processing very large datasets over commodity clusters can be done simply, given the right programming model and infrastructure. In this paper, we describe the design and implementation of the Sector storage cloud and the Sphere compute cloud. By contrast with the existing storage…
Mei Chen
One of the most effective approaches to improve resource usage efficiency and degree of resource collecting is to integrate resources. Many studies on the integration of information resources are also available. The search engines are the most well-known. At the same time, this article intends to optimize the…
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…
Zhipeng Gui, Manzhu Yu, Chaowei Yang, Yunfeng Jiang + 8 more
'Jizhe Xia' 'Qunying Huang' 'Kai Liu' 'Zhenlong Li' 'Mohammed Anowarul Hassan' 'Baoxuan Jin' 'M. Sohel Rahman'] Dust storm has serious disastrous impacts on environment, human health, and assets. The developments and applications of dust storm models have contributed significantly to better understand and predict the…
Authors not listed
Machine learning models are transforming data-driven research across scientific disciplines, yet their deployment as accessible and reliable web services remains a significant challenge. We introduce the NERDD framework, a scalable, maintainable, and secure microservices platform designed to support the sustainable…
Malcolm Sim, Mohammad Ghazi Vakili, Felix Strieth-Kalthoff, Han Hao + 4 more
Self-driving laboratories (SDLs), which combine automated experimental hardware with computational experiment planning, have emerged as powerful tools for accelerating materials discovery. The intrinsic complexity created by their multitude of components requires an effective orchestration platform to ensure the…
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
Computing electrostatic interactions remains the bottleneck of molecular dynamics (MD) simulations despite more than a century of effort in developing methods to accelerate the calculation. Previously we have developed the Spherical Grid and Treecode (SGT) and Gauss-Legendre-Spherical-t (GLST) algorithms for…
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…
Rika Kobayashi, Theodorus P. M. Gouman, N. Ole Carstensen, Thomas M. Soini + 11 more
The COVID-19 pandemic disrupted chemistry teaching practices globally as many courses were forced online necessitating adaptation to the digital platform. The biggest impact was to the practical component of the chemistry curriculum – the so-called wet lab. Naively, it would be thought that computer-based teaching labs…