Application of MATLAB Parallel Programming Technology

2014 ◽  
Vol 602-605 ◽  
pp. 3787-3790
Author(s):  
Song Chi
Keyword(s):  
Parallel Computing ◽  
Parallel Programming ◽  
Program Development ◽  
Computer Simulations ◽  
Develop Method ◽  
Computing Technology ◽  
Parallel And Distributed Computing ◽  
Application Development ◽  
Parallel Application ◽  
Development Technology

The parallel application program development technology and process is analyzed based on the MATLAB parallel and distributed computing toolbox. Hereby, the comparison of the serial computing and the parallel computing is done by computer simulations, and the parallel computing program design and develop method is proposed. The simulations results show that, the parallel computing technology has many advantages in the calculation of high intensive and it is convenience of the parallel application development using MATLAB.

Parallel computing

2018 ◽  
Author(s):  
Joseph F. Boudreau ◽  
Eric S. Swanson
Keyword(s):  
Monte Carlo ◽  
Parallel Computing ◽  
High Performance Computing ◽  
Parallel Programming ◽  
High Performance ◽  
Parallel Application ◽  
Client Server ◽  
Parallel Code ◽  
Performance Computing

This chapter describes various approaches to concurrency, or “parallel programming”. An overview of high performance computing is followed with a review of Flynn’s taxonomy of parallel computing. Three methods for implementing parallel code using the frameworks provided by MPI, openMP, and C++ threads are presented. The use of the C++ constructs mutex and future to resolve issues of synchronization are discussed. All methods are illustrated with an embarrassingly parallel application to a Monte Carlo integral and common pitfalls are presented. The chapter closes with a discussion and example of the utility of forking processes and the use of C++ sockets and their application in a client/server environment.

Parallel Computing Using the Prefix Problem

1994 ◽  
Author(s):  
S. Lakshmivarahan ◽  
Sudarshan K. Dhall
Keyword(s):  
Parallel Computing ◽  
Parallel Algorithms ◽  
Parallel Programming ◽  
Building Blocks ◽  
Efficient Solutions ◽  
Computer Scientists ◽  
Important Approach

The prefix operation on a set of data is one of the simplest and most useful building blocks in parallel algorithms. This introduction to those aspects of parallel programming and parallel algorithms that relate to the prefix problem emphasizes its use in a broad range of familiar and important problems. The book illustrates how the prefix operation approach to parallel computing leads to fast and efficient solutions to many different kinds of problems. Students, teachers, programmers, and computer scientists will want to read this clear exposition of an important approach.

Application of parallel programming method for 3D MHD computer simulations of magnetic reconnection in plasma

2004 ◽  
pp. 373-379
Author(s):  
D.P. Kostomarov ◽  
I.N. Inovenkov ◽  
E.Y. Echkina ◽  
A.V. Leonenko ◽  
O.A. Pavlova ◽  
...  
Keyword(s):  
Magnetic Reconnection ◽  
Parallel Programming ◽  
Computer Simulations ◽  
Programming Method

scholarly journals New Computing Technology in Reliability Engineering

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Radim Briš ◽  
Simona Domesová
Keyword(s):  
Parallel Computing ◽  
High Performance ◽  
Rapid Development ◽  
Computation Time ◽  
Scientific Discipline ◽  
Reliability Engineering ◽  
Computing Technology ◽  
Source Codes ◽  
Computation Efficiency ◽  
Cuda Technology

Reliability engineering is relatively new scientific discipline which develops in close connection with computers. Rapid development of computer technology recently requires adequate novelties of source codes and appropriate software. New parallel computing technology based on HPC (high performance computing) for availability calculation will be demonstrated in this paper. The technology is particularly effective in context with simulation methods; nevertheless, analytical methods are taken into account as well. In general, basic algorithms for reliability calculations must be appropriately modified and improved to achieve better computation efficiency. Parallel processing is executed by two ways, firstly by the use of the MATLAB function parfor and secondly by the use of the CUDA technology. The computation efficiency was significantly improved which is clearly demonstrated in numerical experiments performed on selected testing examples as well as on industrial example. Scalability graphs are used to demonstrate reduction of computation time caused by parallel computing.

scholarly journals Using Cuda and Blockchain Technologies to Recover an Encrypted Pdf File Password

2020 ◽  
pp. 54-60
Author(s):  
V. P. Kvasnikov ◽  
A. S. Dudnik ◽  
O. O. Pysarchuk ◽  
T. S. Domkiv
Keyword(s):  
Parallel Computing ◽  
Statistical Analysis ◽  
Experimental Studies ◽  
Central Processing Unit ◽  
Processing Unit ◽  
Computing Technology ◽  
Graphics Processor ◽  
Central Processing ◽  
Blockchain Technology ◽  
Computational Speed

The article presents an algorithm for using parallel computing technology using CUDA and blockchain technology to recover the password for an encrypted PDF file. The analysis and comparison of the computational speed using a graphics processor (GPU) and a central processing unit (CPU) are carried out. The testing of the implemented algorithm is carried out. A statistical analysis of the results of experimental studies is presented.

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