scholarly journals Research Activity in Computational Physics utilizing High Performance Computing: Co-authorship Network Analysis

2016 ◽  
Vol 759 ◽  
pp. 012091
Author(s):  
Sul-Ah Ahn ◽  
Youngim Jung
Author(s):  
V. HERNÁNDEZ ◽  
A. M. VIDAL ◽  
F. ALVARRUIZ ◽  
J. M. ALONSO ◽  
D. GUERRERO ◽  
...  

2011 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
M Madlazim ◽  
Bagus Jaya Santosa

Python is a relatively new computing language, created by Guido van Rossum [A.S. Tanenbaum, R. van Renesse, H. van Staveren, G.J. Sharp, S.J. Mullender, A.J. Jansen, G. van Rossum, Experiences with the Amoeba distributed operating system, Communications of the ACM 33 (1990) 46–63; also on-line at http://www.cs.vu.nl/pub/amoeba/, which is particularly suitable for teaching a course in computational physics. There are two questions to be considered: (i) For whom is the course intended? (ii) What are the criteria for a suitable language, and why choose Python? The criteria include the nature of the application. High performance computing requires a compiled language, e.g., FORTRAN. For some applications a computer algebra, e.g., Maple, is appropriate. For teaching, and for program development, an interpreted language has considerable advantages: Python appears particularly suitable. Python‟s attractions include (i) its system of modules which makes it easy to extend, (ii) its excellent graphics (VPython module), (iii) its excellent on line documentation, (iv) it is free and can be downloaded from the web. Python and VPython will be described briefly, and some programs demonstrated numerical and animation of some phenomenal physics. In this article, we gave solution of circle polarization by solving Maxwell equation.


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.


2009 ◽  
Vol 29 (8) ◽  
pp. 2132-2135
Author(s):  
Wei PAN ◽  
Liao-yuan CHEN ◽  
Yong-ge LI ◽  
Jin-hua ZHANG ◽  
Li PAN ◽  
...  

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

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