scholarly journals Performance Assessment of Multi-node Parallel Computing System from First-principles

2021 ◽  
Vol 05 (08) ◽  
pp. 82-87
Author(s):  
Mohammed B ◽  
Wante H.P ◽  
Hayatu A
Keyword(s):  
Parallel Computing ◽  
Performance Assessment ◽  
First Principles ◽  
Computing System

Fast Three Dimensional Visualization Using a Parallel Computing System

1989 ◽  
pp. 747-751 ◽  
Author(s):  
U. Kliegis ◽  
R. Neumann ◽  
Th. Kortmann ◽  
W. Schwesig ◽  
R. Mittelstädt ◽  
...  
Keyword(s):  
Parallel Computing ◽  
Three Dimensional ◽  
Computing System

Large Scale Mosaic Using Parallel Computing for Remote Sensed Images

2014 ◽  
Vol 556-562 ◽  
pp. 4746-4749
Author(s):  
Bin Chu ◽  
Da Lin Jiang ◽  
Bo Cheng
Keyword(s):  
Parallel Computing ◽  
High Performance Computing ◽  
High Performance ◽  
Large Scale ◽  
Computing System ◽  
Physical Relationship ◽  
High Performance Computing System ◽  
Performance Computing

This paper concerns about Large-scale mosaic for remote sensed images. Base on High Performance Computing system, we offer a method to decompose the problem and integrate them with logical and physical relationship. The mosaic of Large-scale remote sensed images has been improved both at performance and effectiveness.

A Deep Web Data Extraction and Application System Based on Cloud Technology

2013 ◽  
Vol 756-759 ◽  
pp. 2583-2587 ◽  
Author(s):  
Zi Yang Han ◽  
Feng Ying Wang ◽  
Ping Sun ◽  
Zheng Yu Li
Keyword(s):  
Parallel Computing ◽  
Data Extraction ◽  
Scheduling Algorithm ◽  
Computing System ◽  
Extraction Process ◽  
Deep Web ◽  
System Structure ◽  
Web Data ◽  
Cloud Technology ◽  
Web Data Extraction

There are so many Deep Webs in Internet, which contains a large amount of valuable data, This paper proposes a Deep Web data extraction and service system based on the principle of cloud technology. We adopt a kind of multi-node parallel computing system structure and design a task scheduling algorithm in the data extraction process, in above foundation, balance the task load of among nodes to accomplish data extraction rapidly; The experimental results show that cloud parallel computing and dispersed network resources are used to extract data in Deep Web system is valid and improves the data extraction efficiency of Deep Web and service quality.

A Hybrid Parallelizable Algorithm for Computer Simulation of Rigid Body Molecular Dynamics

2007 ◽  
Author(s):  
Shanzhong Duan
Keyword(s):  
Molecular Dynamics ◽  
Computer Simulation ◽  
Parallel Computing ◽  
Rigid Body ◽  
Computing System ◽  
Rigid Body Dynamics ◽  
Constraint Forces ◽  
Explicit Determination ◽  
Motion Behavior

Molecular dynamics is effective for a nano-scale phenomenon analysis. This paper presents a hybrid parallelizable algorithm for the computer simulation of the motion behavior of molecular chain and open-tree structure on parallel computing system. The algorithm is developed from an approach of rigid body dynamics, in which interbody constraints are exposed so that a system of largely independent multibody subchains is formed. The increased parallelism is obtainable through bringing interbody constraints to evidence and the explicit determination of the associated constraint forces combined with a sequential O(n) procedure. Each subchain then is assigned to a processor for parallel computing. The algorithm offers a sequential O(n) performance if there is only one processor available. The algorithm has O(log2n) computational efficiency if there are as many processors available as number for molecular bodies. For most common scenario, the algorithm will give a computational complexity between O(n) and O(log2n) if number of available processor is less than number of molecular bodies.

PARDEC: A Parallel Decomposition Algorithm for Non-Hierarchical Systems or Structures

1994 ◽  
Author(s):  
Hans A. Eschenauer ◽  
Matthias Weinert
Keyword(s):  
Parallel Computing ◽  
Shape Optimization ◽  
Optimization Problems ◽  
Computing System ◽  
Decomposition Algorithm ◽  
Hierarchical Systems ◽  
Parallel Decomposition

Abstract The present paper introduces a decomposition algorithm for non-hierarchical systems or structures. The algorithm coordinates the created subsystem optimization problems by means of an approximation strategy. It is implemented on a parallel computing system and will be verified on shape optimization problems.

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