Spreading High Performance Computing Skills with E-Learning Support

Author(s):  
M. Melichercik ◽  
V. Siladi ◽  
M. Svitek ◽  
L. Huraj
Author(s):  
Laimonis Zacs ◽  
Anita Jansone

<p><em>In this paper the authors describe solution for solving various analytical problems in <em>E-learning, Course Management Systems like Moodle by using HPC</em></em> <em>(High Performance Computing) and Apache Hadoop open source technologies in Liepaja University. The problem is that nowadays there are collecting huge amounts of analytics data from several gigabytes to petabytes, which is hard to store, process, analyse and visualize. This article reflects one of the solutions concerning distributed parallel processing of huge amounts of data across inexpensive, industry-standard servers that can store and process the data, can scale without limits and provides technological opportunities of reliable, scalable and distributed computing.</em><em> </em></p><p> </p>


Author(s):  
Meruert Serіk ◽  
Gulmira Yerlanova ◽  
Nursaule Karelkhan ◽  
Nurlykhan Temirbekov

The need for specialists with high-performance computing skills is growing day by day. This is due to the fact that the high-performance process of processing big data is one of the most pressing problems today. This is especially important in science, economics, physical modeling, medicine, bioinformatics, weather forecasting, etc. This article analyzes the conditions for teaching high-performance computing, the experience of leading universities in the world, and it is established that teaching high-performance computing requires study. High performance computing training was carried out on 3 different hardware equipment (a personal computer, a supercomputer “Param-Bilim” India – Kazakhstan Centre of Excellence in ICT [IKCOEICT] at L.N. Gumilyov Eurasian National University and a quantum computer in the cloud IBM Quantum Experience) using different algorithms in the C ++ and Phyton programming languages. The effectiveness of the calculation results in the educational process was determined as a result of the completed questionnaire.


MRS Bulletin ◽  
1997 ◽  
Vol 22 (10) ◽  
pp. 5-6
Author(s):  
Horst D. Simon

Recent events in the high-performance computing industry have concerned scientists and the general public regarding a crisis or a lack of leadership in the field. That concern is understandable considering the industry's history from 1993 to 1996. Cray Research, the historic leader in supercomputing technology, was unable to survive financially as an independent company and was acquired by Silicon Graphics. Two ambitious new companies that introduced new technologies in the late 1980s and early 1990s—Thinking Machines and Kendall Square Research—were commercial failures and went out of business. And Intel, which introduced its Paragon supercomputer in 1994, discontinued production only two years later.During the same time frame, scientists who had finished the laborious task of writing scientific codes to run on vector parallel supercomputers learned that those codes would have to be rewritten if they were to run on the next-generation, highly parallel architecture. Scientists who are not yet involved in high-performance computing are understandably hesitant about committing their time and energy to such an apparently unstable enterprise.However, beneath the commercial chaos of the last several years, a technological revolution has been occurring. The good news is that the revolution is over, leading to five to ten years of predictable stability, steady improvements in system performance, and increased productivity for scientific applications. It is time for scientists who were sitting on the fence to jump in and reap the benefits of the new technology.


2001 ◽  
Author(s):  
Donald J. Fabozzi ◽  
Barney II ◽  
Fugler Blaise ◽  
Koligman Joe ◽  
Jackett Mike ◽  
...  

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