scholarly journals Comparison of Swarm Optimization and Memetic Algorithm for Systolic Mapping of Texture Analysis

2020 ◽  
pp. 393-400
Author(s):  
Bagavathi C ◽  
Dhivya devi R ◽  
Siddharthraju K ◽  
Dinesh P
Keyword(s):  
Texture Analysis ◽  
Systolic Array ◽  
Parallel Architecture ◽  
Memetic Algorithms ◽  
Utilization Efficiency ◽  
Design Data ◽  
Systolic Architecture ◽  
Swarm Optimization ◽  
Industrial Processing ◽  
Mapping Techniques

Systolic processors offer a hardware design which can accommodate more functions in a small footprint. Hardware utilization efficiency can be enhanced by appropriately designating the intended hardware with a task in space and time through parallel computing platforms. Regular algorithms known for their computational complexity can be mapped to systolic array by dependence graphs, which allot hardware to the design data. Manual mapping techniques tend to be tedious with more inaccuracy and calls for efficient mapping techniques, automated through algorithmic procedures. Texture Analysis marks the preliminary progression of image analysis and interpretation. Automotive systems, Robotics, Industrial processing and similar automated applications can be simplified through texture analysis. This work deals with employing evolutionary algorithms for mapping texture analysis onto systolic architecture. Memetic Algorithms (MA) and Particle Swarm Optimization (PSO) algorithms were comparatively studied and the efficiency of designing a parallel architecture through systolic array is analyzed through cost function and processing time.

High speed modular systolic array-based DTCWT with parallel processing architecture for 2D image transformation on FPGA

2017 ◽  
Vol 15 (05) ◽  
pp. 1750047 ◽  
Author(s):  
S. S. Divakara ◽  
Sudarshan Patilkulkarni ◽  
Cyril Prasanna Raj
Keyword(s):  
Systolic Array ◽  
High Speed ◽  
Parallel Architecture ◽  
Software Implementation ◽  
Wavelet Filter ◽  
Image Transformation ◽  
Complex Wavelet Transform ◽  
Pipelined Architecture ◽  
Array Architecture ◽  
Processing Architecture

In this paper, systolic array-based novel architecture for dual-tree complex wavelet transform (DTCWT) computation is designed and implemented on FPGA. The wavelet filter coefficients of DTCWT are quantized and rounded to nearest integer and the loss in rounding and quantization is limited to 0.5[Formula: see text]dB as compared with software implementation. The parallel architecture designed computes row elements simultaneously and pipelined architecture is designed to compute column elements. The proposed architecture is modeled using Verilog and implemented on Xilinx Virtex II FPGA. For 2D implementation, the design operates at a maximum frequency of 156[Formula: see text]MHz and consumes power less than 3[Formula: see text]W. This is the first design with systolic array architecture on FPGA for DTCWT computation operating at frequencies greater than 100[Formula: see text]MHz.

scholarly journals Programação da produção e meta-heurísticas: uma revisão de mapeamento sistemático

2018 ◽  
Vol 14 (3) ◽  
Author(s):  
Ailton Silva Ferreira ◽  
Hussein Adnen Mustafa ◽  
Cristiano Manhães Oliveira ◽  
Tiago Andrade Muniz Terra ◽  
Thiago Dan Said
Keyword(s):  
Genetic Algorithms ◽  
Particle Swarm Optimization ◽  
Simulated Annealing ◽  
Web Of Science ◽  
Harmony Search ◽  
Evolutionary Programming ◽  
Memetic Algorithms ◽  
Hill Climbing ◽  
Swarm Optimization ◽  
Page Rank

A Programação da Produção tem recebido atenção de pesquisadores da área de Pesquisa Operacional desde a década de 50 e um grande número de trabalhos foi desenvolvido desde então, da mesma forma, devido à Internet, o rastreamento bibliográfico de um campo de pesquisa está vez mais demorado, como também encontrar relações entre autores e publicações relevantes, está ficando cada vez mais difícil, devido ao crescente volume de informações. Dessa forma, este trabalho busca realizar uma revisão de mapeamento sistemático, com relação à programação da produção e algumas das principais meta-heurísticas (Hill Climbing, Simulated Annealing, TabuSearch,Harmony Search, GRASP, Evolutionary Algorithms, Genetic Algorithms, Evolution Strategies, Genetic Programming, Differencia lEvolution, Evolutionary Programming, Particle Swarm Optimization, Memetic Algorithms e Ant Colony), através de indicadores bibliométricos  e análise de redes (Page Rank), busca-se demonstrar a relação de artigos, autores e publicações mais importantes e de maior prestígio de dados originados da base Web of Science com auxílio das ferramentas NAILS e GEPHI. Finalmente, é demonstrado que a utilização de meta-heurísticas na Programação da Produção - PP, apesar de ser uma linha de pesquisa antiga, ainda se mantém com grande interesse e em constante desenvolvimento.   

scholarly journals A Systolic Array-Based FPGA Parallel Architecture for the BLAST Algorithm

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Xinyu Guo ◽  
Hong Wang ◽  
Vijay Devabhaktuni
Keyword(s):  
Systolic Array ◽  
Clock Cycle ◽  
Parallel Architecture ◽  
Second Step ◽  
Local Alignment ◽  
Alignment Algorithm ◽  
Biological Sequence ◽  
Sequence Alignment Algorithm ◽  
Field Programmable ◽  
Search Tool

A design of systolic array-based Field Programmable Gate Array (FPGA) parallel architecture for Basic Local Alignment Search Tool (BLAST) Algorithm is proposed. BLAST is a heuristic biological sequence alignment algorithm which has been used by bioinformatics experts. In contrast to other designs that detect at most one hit in one-clock-cycle, our design applies a Multiple Hits Detection Module which is a pipelining systolic array to search multiple hits in a single-clock-cycle. Further, we designed a Hits Combination Block which combines overlapping hits from systolic array into one hit. These implementations completed the first and second step of BLAST architecture and achieved significant speedup comparing with previously published architectures.

scholarly journals Energy Storage Coordination in Energy Internet Based on Multi-Agent Particle Swarm Optimization

2018 ◽  
Vol 8 (9) ◽  
pp. 1520 ◽  
Author(s):  
Jicheng Liu ◽  
Dandan He ◽  
Qiushuang Wei ◽  
Suli Yan
Keyword(s):  
Particle Swarm Optimization ◽  
Energy Storage ◽  
Particle Swarm ◽  
Energy Utilization ◽  
Utilization Efficiency ◽  
Swarm Optimization ◽  
Energy Internet ◽  
Energy Networks ◽  
Multi Agent ◽  
Agent Particle

With the rapid development of energy Internet (EI), energy storage (ES), which is the key technology of EI, has attracted widespread attention. EI is composed of multiple energy networks that provide energy support for each other, so it has a great demand for diverse energy storages (ESs). All of this may result in energy redundancy throughout the whole EI system. Hence, coordinating ESs among various energy networks is of great importance. First of all, we put forward the necessity and principles of energy storage coordination (ESC) in EI. Then, the ESC model is constructed with the aim of economic efficiency (EE) and energy utilization efficiency (EUE) respectively. Finally, a multi-agent particle swarm optimization (MAPSO) algorithm is proposed to solve this problem. The calculation results are compared with that of PSO, and results show that MAPSO has good convergence and computational accuracy. In addition, the simulation results prove that EE plays the most important role when coordinating various ESs in EI, and an ES configuration with the multi-objective optimization of EE and EUE is concluded at last.

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