scholarly journals Computational physics Using Python: Implementing Maxwell Equation for Circle Polarization

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.

2018 ◽  
Author(s):  
Gabriel B. Moro ◽  
Lucas Mello Schnorr

Performance and energy consumption are fundamental requirements in computer systems. A very frequent challenge is to combine both aspects, searching to keep the high performance computing while consuming less energy. There are a lot of techniques to reduce energy consumption, but in general, they use modern processors resources or they require specific knowledge about application and platform used. In this paper, we propose a library that dynamically changes the processor frequency according to the application's computing behavior, using a previous analysis of its Memory-Bound regions. The results show a reduction of 1,89% in energy consumption for Lulesh application with an increase of 0,09% in runtime when we compare our approach against the governor Ondemand of the Linux Operating System.


2007 ◽  
Vol 20 (1) ◽  
pp. 31-43 ◽  
Author(s):  
Dragan Simic ◽  
Srecko Ristic ◽  
Slobodan Obradovic

This paper describes the methods and means used for creating a computer cluster using ordinary PCs. The cluster is running a replicated relational database, and two custom Web applications, used as the database clients. Operating system running all this is Linux 2.4, with Linux Virtual Server (LVS) used as the load-balancing solution, MySQL 4.0 as the replicated database (supporting transactions and referential integrity), and Apache 1.3 as the Web server. PHP4 is used for Web applications development. Additionally, a High Performance Computing (HPC) cluster is implemented using OpenMOSIX. Measurement and comparison of achieved performance levels is done as the final aim, using two custom applications developed for that purpose, acting as clients of two deployed Web applications. Performance-measurement applications are running under Microsoft Windows, and are developed using Borland Delphi 7.


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