Co-simulation of electric ship power and control systems using high performance computing

Author(s):  
Michael S. Mazzola ◽  
Tomasz Haupt ◽  
Gregory Henley ◽  
Angela Card ◽  
Jian Shi
Author(s):  
Gennady Shvachych ◽  
Nina Rizun ◽  
Olena Kholod ◽  
Olena Ivaschenko ◽  
Volodymyr Busygin

The chapter analyzes the ways of development of high-performance computing systems. It is shown that a real breakthrough in mastering parallel computing technologies can be achieved by developing an additional (actually basic) level in the hierarchy of hardware capacities of multiprocessor computing systems of MPP-architecture, the personal computing clusters. Thus, it is proposed to create the foundation of the hardware pyramid of parallel computing technology in the form of personal computing clusters. It is shown that on the basis of multiprocessor information systems processing and control, the control systems are implemented for many industries: space industry, aviation, air defense and anti-missile defense systems, and many others. However, the production of multiprocessor information processing and control systems is hampered by high cost at all its stages. As a result, the total cost of the system often makes it as an inaccessible tool. The use of modern multiprocessor cluster systems would reduce the costs of its production.


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.


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