Cu-T-Pi Revised: An Updated Model Supercomputer for Parallel Computing Pedagogy

2020 ◽  
pp. 527-535
Author(s):  
James Wolfer
Keyword(s):  
Parallel Computing

Introduction to Parallel Computing

2016 ◽  
Author(s):  
Zbigniew J. Czech
Keyword(s):  
Parallel Computing

Parallel Computing in Optimization

1998 ◽  
Vol 49 (7) ◽  
pp. 770-771
Author(s):  
V J Rayward-Smith
Keyword(s):  
Parallel Computing

Methods and Technologies of Parallel Computing for Mathematical Modeling of Stress-Strain State of Constructions Taking into Account Ductile Fracture

2014 ◽  
Vol 46 (11) ◽  
pp. 23-35 ◽  
Author(s):  
Elena A. Velikoivanenko ◽  
Alexey S. Milenin ◽  
Alexander V. Popov ◽  
Vladimir A. Sidoruk ◽  
Alexander N. Khimich
Keyword(s):  
Mathematical Modeling ◽  
Parallel Computing ◽  
Ductile Fracture ◽  
Strain State ◽  
Stress Strain ◽  
Stress Strain State

Matlab and Parallel Computing

2012 ◽  
Vol 17 (4) ◽  
pp. 207-216 ◽  
Author(s):  
Magdalena Szymczyk ◽  
Piotr Szymczyk
Keyword(s):  
Image Processing ◽  
Signal Processing ◽  
Parallel Computing ◽  
Distributed Computing ◽  
Control Systems ◽  
High Performance ◽  
Parallel Applications ◽  
Process Simulations ◽  
Key Features ◽  
Financial Process

Abstract The MATLAB is a technical computing language used in a variety of fields, such as control systems, image and signal processing, visualization, financial process simulations in an easy-to-use environment. MATLAB offers "toolboxes" which are specialized libraries for variety scientific domains, and a simplified interface to high-performance libraries (LAPACK, BLAS, FFTW too). Now MATLAB is enriched by the possibility of parallel computing with the Parallel Computing ToolboxTM and MATLAB Distributed Computing ServerTM. In this article we present some of the key features of MATLAB parallel applications focused on using GPU processors for image processing.

Sign in / Sign up

Export Citation Format

Share Document