An efficient task scheduling for weather forecasting suites in high performance computing

2021 ◽  
Author(s):  
Rintu Nath ◽  
A. Nagaraju
Keyword(s):  
High Performance Computing ◽  
Task Scheduling ◽  
High Performance ◽  
Weather Forecasting ◽  
Performance Computing

scholarly journals Contemporary Perception Of Task Scheduling Techniques In Cloud: A Review

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Cloud Computing ◽  
High Performance Computing ◽  
Task Scheduling ◽  
High Performance ◽  
Communications Technology ◽  
Small Companies ◽  
Network Access ◽  
On Demand ◽  
Computing Services ◽  
Performance Computing

Typically, the constant changes in computers and communications technology led to the need of on-demand network access to a shared computing resources to reduce cost and time and this is known as Cloud computing, which delivers computing services to users as a pay-as-you-go manner by emerging several distributed and high performance computing concepts. The cloud makes reaching any information or source possible from anywhere eliminating the setup and instillation step such that the user and the hardware may co-exist in different places. This comes beneficial for the users or the small companies that cannot effort to pay for the hardware, storage or resources as the big companies. Many of the studies on cloud computing was dedicated to the performance efficiency of task scheduling. Scheduling is a wide concept and it is one of the most important issues that generally work on mapping tasks to appropriate resources efficiently and effectively using one or more strategy. This paper have reviewed and classified the most recent scheduling algorithms in cloud computing and gave examples on each.

scholarly journals The Use of The High-Performance Computing in The Learning Process

2021 ◽  
Vol 16 (17) ◽  
pp. 240
Author(s):  
Meruert Serіk ◽  
Gulmira Yerlanova ◽  
Nursaule Karelkhan ◽  
Nurlykhan Temirbekov
Keyword(s):  
High Performance Computing ◽  
Programming Languages ◽  
High Performance ◽  
Weather Forecasting ◽  
Quantum Computer ◽  
Educational Process ◽  
Computing Skills ◽  
National University ◽  
Calculation Results ◽  
Performance Computing

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.

The Recent Revolution in High Performance Computing

MRS Bulletin ◽  
1997 ◽  
Vol 22 (10) ◽  
pp. 5-6
Author(s):  
Horst D. Simon
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
New Technologies ◽  
New Technology ◽  
Parallel Architecture ◽  
Time Frame ◽  
Good News ◽  
Computing Industry ◽  
Time And Energy ◽  
Performance Computing

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.

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