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Alejandro Valencia-Arias, Juan David González-Ruiz, Lilian Verde Flores, Luis Vega-Mori, Paula Rodríguez-Correa and Gustavo Sánchez Santos
Machine learning and blockchain technology are fast-developing fields with implications for multiple sectors. Both have attracted a lot of interest and show promise in security, IoT, 5G/6G networks, artificial intelligence, and more. However, challenges ...
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Md Azam Hossain, Soonwook Hwang and Jik-Soo Kim
Scientific applications often require substantial amount of computing resources for running challenging jobs potentially consisting of many tasks from hundreds of thousands to even millions. As a result, many institutions collaborate to solve large-scale...
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Lili Liang, Yufeng Hu, Zhiwu Liu, Yuntao Ye, Kuang Li, Kexin Liu, Haiqing Xu and Xiquan Liu
The lumped hydrological model and empirical model have the problems of low accuracy and short forecasting period in real-time flood forecasting of small- and medium-sized rivers in a mountainous watershed. The sharing of underlying surface data such as h...
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Jabanjalin Hilda and Srimathi Chandrasekaran
A heterogeneous system can be portrayed as a variety of unlike resources that can be locally or geologically spread, which is exploited to implement data-intensive and computationally intensive applications. The competence of implementing the scientific ...
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Min Thu Khaing,Sergey Lupin,Aung Thu
Pág. 30 - 36
Nowadays, distributed computing is one of the popular approaches that is widely used in research and development related to the use of resource-intensive applications. The available distributed computing systems are based on modern GRID technologies. The...
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V. N. Yakimets,I. I. Kurochkin
Pág. 1 - 8
Desktop grid systems have been used to solve scientific problems for more than twenty years. The use of computing resources of volunteers allows you to organize distributed systems consisting of tens and hundreds of thousands of nodes. The computational ...
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Denis Shaikhislamov,Andrey Sozykin,Vadim Voevodin
Pág. 57 - 83
Neural networks are becoming more and more popular in scientific field and in the industry. It is mostly because new solutions using neural networks show state-of-the-art results in the domains previously occupied by traditional methods, eg. computer vis...
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Ling Xu, Jianzhong Qiao, Shukuan Lin and Wanting Zhang
Volunteer computing (VC) is a distributed computing paradigm, which provides unlimited computing resources in the form of donated idle resources for many large-scale scientific computing applications. Task scheduling is one of the most challenging proble...
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Gabriel Noaje,Alan Davis,Jonathan Low,Seng Lim,Geok Lian Tan,Lukasz Orlowski,Dominic Chien,Sing-Wu Liou,Tin Wee Tan,Yves Poppe,Kenneth Ban Hon Kim,Andrew Howard,David Southwell,Jason Gunthorpe,Marek Michalewicz
Pág. 87 - 102
The global effort to build ever more powerful supercomputers is faced with the challenge of ramping up High Performance Computing systems to ExaScale capabilities and, at the same time, keeping the electrical power consumption for a system of that scale ...
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