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Wyświetlanie 1-4 z 4
Tytuł:
Particle Swarm Optimization Algorithm for Leakage Power Reduction in VLSI Circuits
Autorzy:
Leela Rani, V.
Madhavi Latha, M.
Powiązania:
https://bibliotekanauki.pl/articles/225990.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
leakage power
PSO algorithm
genetic algorithm
minimum leakage vector
Verilog-HDL implementation
Opis:
Leakage power is the dominant source of power dissipation in nanometer technology. As per the International Technology Roadmap for Semiconductors (ITRS) static power dominates dynamic power with the advancement in technology. One of the well-known techniques used for leakage reduction is Input Vector Control (IVC). Due to stacking effect in IVC, it gives less leakage for the Minimum Leakage Vector (MLV) applied at inputs of test circuit. This paper introduces Particle Swarm Optimization (PSO) algorithm to the field of VLSI to find minimum leakage vector. Another optimization algorithm called Genetic algorithm (GA) is also implemented to search MLV and compared with PSO in terms of number of iterations. The proposed approach is validated by simulating few test circuits. Both GA and PSO algorithms are implemented in Verilog HDL and the simulations are carried out using Xilinx 9.2i. From the simulation results it is found that PSO based approach is best in finding MLV compared to Genetic based implementation as PSO technique uses less runtime compared to GA. To the best of the author’s knowledge PSO algorithm is used in IVC technique to optimize power for the first time and it is quite successful in searching MLV.
Źródło:
International Journal of Electronics and Telecommunications; 2016, 62, 2; 179-186
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Soft X-ray Diagnostic System Upgrades and Data Quality Monitoring Features for Tokamak Usage
Autorzy:
Wojenski, Andrzej
Linczuk, Paweł
Piotr, Kolasinski
Chernyshova, Maryna
Mazon, Didier
Kasprowicz, Grzegorz
Pozniak, Krzysztof T.
Gaska, Michał
Czarski, Tomasz
Krawczyk, Rafał
Powiązania:
https://bibliotekanauki.pl/articles/1844595.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
data quality monitoring
FPGA
Verilog/VHDL
HDL
GEM detector
SXR plasma diagnostics
modular measurement system
data evaluation
tokamak
Opis:
The validation of the measurements quality after on-site diagnostic system installation is necessary in order to provide reliable data and output results. This topic is often neglected or not discussed in detail regarding measurement systems. In the paper recently installed system for soft X-ray measurements is described in introduction. The system is based on multichannel GEM detector and the data is collected and sent in special format to PC unit for further postprocessing. The unique feature of the system is the ability to compute final data based on raw data only. The raw data is selected upon algorithms by FPGA units. The FPGAs are connected to the analog frontend of the system and able to register all of the signals and collect the useful data. The interface used for data streaming is PCIe Gen2 x4 for each FPGA, therefore high throughput of the system is ensured. The paper then discusses the properties of the installation environment of the system and basic functionality mode. New features are described, both in theoretical and practical approach. New modes correspond to the data quality monitoring features implemented for the system, that provide extra information to the postprocessing stage and final algorithms. In the article is described also additional mode to perform hardware simulation of signals in a tokamak-like environment using FPGAs. The summary describes the implemented features of the data quality monitoring features and additional modes of the system.
Źródło:
International Journal of Electronics and Telecommunications; 2021, 67, 1; 109-114
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Advanced Real-time Evaluation and Data Quality Monitoring Model Integration with FPGAs for Tokamak High-performance Soft X-ray Diagnostic System
Autorzy:
Wojenski, A.
Poźniak, K.
Mazon, D.
Chernyshova, M.
Powiązania:
https://bibliotekanauki.pl/articles/227260.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
data quality monitoring
system modeling
FPGA
Verilog/VHDL
HDL
GEM detector
SXR plasma diagnostics
modular measurement system
data evaluation
Opis:
Based on the publications regarding new or recent measurement systems for the tokamak plasma experiments, it can be found that the monitoring and quality validation of input signals for the computation stage is done in different, often simple, ways. In the paper is described the unique approach to implement the novel evaluation and data quality monitoring (EDQM) model for use in various measurement systems. The adaptation of the model is made for the GEM-based soft X-ray measurement system FPGA-based. The EDQM elements has been connected to the base firmware using PCI-E DMA real-time data streaming with minimal modification. As additional storage, on-board DDR3 memory has been used. Description of implemented elements is provided, along with designed data processing tools and advanced simulation environment based on Questa software.
Źródło:
International Journal of Electronics and Telecommunications; 2018, 64, 4; 473-479
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An Efficient Classification of Hyperspectral Remotely Sensed Data Using Support Vector Machine
Autorzy:
Mahendra, H. N.
Mallikarjunaswamy, S.
Powiązania:
https://bibliotekanauki.pl/articles/2134051.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
support vector machine
SVM
central processing unit
CPU
digital signal processor
DSP
field programmable gate array
FPGA
high level synthesis
HLS
hardware description language
HDL
Opis:
This work present an efficient hardware architecture of Support Vector Machine (SVM) for the classification of Hyperspectral remotely sensed data using High Level Synthesis (HLS) method. The high classification time and power consumption in traditional classification of remotely sensed data is the main motivation for this work. Therefore presented work helps to classify the remotely sensed data in real-time and to take immediate action during the natural disaster. An embedded based SVM is designed and implemented on Zynq SoC for classification of hyperspectral images. The data set of remotely sensed data are tested on different platforms and the performance is compared with existing works. Novelty in our proposed work is extend the HLS based FPGA implantation to the onboard classification system in remote sensing. The experimental results for selected data set from different class shows that our architecture on Zynq 7000 implementation generates a delay of 11.26 μs and power consumption of 1.7 Watts, which is extremely better as compared to other Field Programmable Gate Array (FPGA) implementation using Hardware description Language (HDL) and Central Processing Unit (CPU) implementation.
Źródło:
International Journal of Electronics and Telecommunications; 2022, 68, 3; 609--617
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

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