Optimization of Layer-based Scheduling Algorithms for Mixed Parallel Applications with Precedence Constraints Using Move-blocks

2009 ◽  
Author(s):  
Raphael Kunis ◽  
Gudula Rünger
Keyword(s):  
Scheduling Algorithms ◽  
Precedence Constraints ◽  
Parallel Applications

scholarly journals Boosted System Performance based on Execution Time Using LiMca Scheduling Algorithm

2021 ◽  
Vol 23 (06) ◽  
pp. 1318-1329
Author(s):  
M. Sreenath ◽  
◽  
Dr. P. A. Vijaya ◽  
Keyword(s):  
Real Time ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Precedence Constraints ◽  
Due Dates ◽  
Real Time Scheduling ◽  
Computational Performance ◽  
Time Scheduling ◽  
The Individual ◽  
Optimum Solution

The scheduling algorithms have been examined by the process of task execution in a system to achieve maximum utilization of multiprocessors. Consequently, the research attempted to propose a new real-time scheduling algorithm to support a multiprocessor platform. The proposed scheduling algorithm, List Mcnaughton’s amalgamation (LiMca) scheduling algorithm has been developed for an optimum solution with the features of List and Mcnaughton’s scheduling algorithms to overcome the individual drawbacks (pre-emption and Precedence constraints). In LiMca, Workload has been distributed to the processors in a system by sorting the tasks in decreasing order with their precedence constraints including due dates, pre-emption, and context switching. In this arena, the LiMca scheduling algorithm has been developed on a traditional avionic mission system and also simulated on a real-time application. The extensive simulations were carried out on the time optimization of resources scheduling (TORSCHE) simulation toolbox. LiMca scheduling algorithm performed superior as compared to recently reported scheduling algorithms like list, hu’s, McNaughton’s, Brucker’s, and Hodgson’s in terms of computational performance.

Capacity-Fairness Controllable Scheduling Algorithms for Single-Carrier FDMA

2014 ◽  
Vol E97.B (7) ◽  
pp. 1474-1482 ◽  
Author(s):  
Takayoshi IWATA ◽  
Hiroyuki MIYAZAKI ◽  
Fumiyuki ADACHI
Keyword(s):  
Scheduling Algorithms ◽  
Single Carrier

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.

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