scholarly journals MULTI-AGENT PARALLEL IMPLEMENTATION OF PHOTOMASK SIMULATION IN PHOTOLITHOGRAPHY

2014 ◽  
pp. 45-54
Author(s):  
Syarhei M. Avakaw ◽  
Alexander A. Doudkin ◽  
Alexander V. Inyutin ◽  
Aleksey V. Otwagin ◽  
Vladislav A. Rusetsky
Keyword(s):  
Parallel Implementation ◽  
Graph Model ◽  
Computing System ◽  
Aerial Image ◽  
Image Simulation ◽  
Time Dynamic ◽  
System A ◽  
Parallel Image Processing ◽  
Parallel Image ◽  
Multi Agent

A framework for paralleling aerial image simulation in photolithography is proposed. Initial data for the simulation representing photomask are considered as a data stream that is processed by a multi-agent computing system. A parallel image processing is based on a graph model of a parallel algorithm. The algorithm is constructed from individual computing operations in a special visual editor. Then the visual representation is converted into XML, which is interpreted by the multi-agent system based on MPI. The system performs run- time dynamic optimization of calculations using an algorithm of virtual associative network. The proposed framework gives a possibility to design and analyze parallel algorithms and to adapt them to architecture of the computing cluster.

DATA ALLOCATION STRATEGIES FOR PARALLEL IMAGE PROCESSING ALGORITHMS

1995 ◽  
Vol 09 (04) ◽  
pp. 615-634 ◽  
Author(s):  
VIRGINIE MARION-POTY ◽  
SERGE MIGUET
Keyword(s):  
Parallel Implementation ◽  
Image Data ◽  
Data Allocation ◽  
Load Imbalance ◽  
Parallel Image Processing ◽  
Parallel Image ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Recursive Operators ◽  
Allocation Strategies

This paper discusses several data allocation strategies used for the parallel implementation of basic imaging operators. It shows that depending on the operator (sequential or parallel, with regular or irregular execution time), the image data must be partitioned in very different manners: The square sub-domains are best adapted for minimizing the communication volume, but rectangles can perform better when we take into account the time for constructing messages. Block allocations are well adapted for inherently parallel operators since they minimize interprocessor interactions, but in the case of recursive operators, they lead to nearly sequential executions. In this framework, we show the usefulness of block-cyclic allocations. Finally, we illustrate the fact that allocating the same amount of image data to each processor can lead to severe load imbalance in the case of some operators with data-dependant execution times.

QUALITY AND COMPLEXITY BOUNDS OF LOAD BALANCING ALGORITHMS FOR PARALLEL IMAGE PROCESSING

2000 ◽  
Vol 14 (04) ◽  
pp. 463-476 ◽  
Author(s):  
SERGE MIGUET ◽  
JEAN-MARC PIERSON
Keyword(s):  
Image Processing ◽  
Parallel Implementation ◽  
Data Distribution ◽  
Complexity Bounds ◽  
Distribution Strategy ◽  
Optimal Partitions ◽  
Parallel Image Processing ◽  
Parallel Image ◽  
The Family

The parallel implementation of image processing algorithms implies an important choice of data distribution strategy. In order to handle the specific constraints associated with images, data distribution must take into account not only the locality of the data and its geometrical regularity but also the possible irregular computation costs associated with different image elements. A widely studied field to tackle this problem is the family of methods related to rectilinear partitioning. We introduce two fully parallel heuristics that compute suboptimal partitions, with a better complexity than the best known algorithms that compute optimal partitions. In this paper, we compare our heuristics to an optimal partitioning, both in terms of execution time and accuracy of the partition. We give some theoretical bounds on the quality of these heuristics that are corroborated by results of random numerical experiments and real applications.

GPU processing for parallel image processing and real-time object recognition

2014 ◽  
Author(s):  
Kevin Vincent ◽  
Damien Nguyen ◽  
Brian Walker ◽  
Thomas Lu ◽  
Tien-Hsin Chao
Keyword(s):  
Image Processing ◽  
Object Recognition ◽  
Real Time ◽  
Parallel Image Processing ◽  
Parallel Image ◽  
Gpu Processing

Modeling of Multi-Agent System for Drilling Simulation

2011 ◽  
Vol 383-390 ◽  
pp. 1555-1561
Author(s):  
Wu Li Wang ◽  
Yan Jiang Wang
Keyword(s):  
Simulation System ◽  
Drilling Process ◽  
Multi Agent System ◽  
Agent System ◽  
Oil Drilling ◽  
Well Control ◽  
Existing Problems ◽  
System A ◽  
Multi Agent ◽  
Drilling Simulation

In view of the characteristics of the oil drilling process and the existing problems of traditional simulation system, a new distributed drilling simulation model was established based on Multi-Agent system (MAS) technology. By means of autonomous, cooperative and reactive characteristic of Agent, the drilling laws and phenomenon can be reflected promptly and accurately under any circumstances. The MAS modeling for oil drilling simulation, the structure and knowledge representation of each Agent and the communication among Agents are described in detail. Finally, an Agent-based normal drilling well control simulation training example was given. The simulation results show that the simulator based on Multi-Agent system has better performances than traditional drilling simulators, and enhances the integrated training function of the drilling simulation system.

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