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Fuzzy Logic Based Power-Efficient Real-Time Multi-Core System (Paperback, 1st ed. 2017) Loot Price: R1,112
Discovery Miles 11 120
Repayment Terms: R104 pm x 12*
Fuzzy Logic Based Power-Efficient Real-Time Multi-Core System (Paperback, 1st ed. 2017): Jameel Ahmed, Mohammed Yakoob Siyal,...

Fuzzy Logic Based Power-Efficient Real-Time Multi-Core System (Paperback, 1st ed. 2017)

Jameel Ahmed, Mohammed Yakoob Siyal, Shaheryar Najam, Zohaib Najam

Series: SpringerBriefs in Computational Intelligence

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Loot Price R1,112 Discovery Miles 11 120 | Repayment Terms: R104 pm x 12*

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This book focuses on identifying the performance challenges involved in computer architectures, optimal configuration settings and analysing their impact on the performance of multi-core architectures. Proposing a power and throughput-aware fuzzy-logic-based reconfiguration for Multi-Processor Systems on Chip (MPSoCs) in both simulation and real-time environments, it is divided into two major parts. The first part deals with the simulation-based power and throughput-aware fuzzy logic reconfiguration for multi-core architectures, presenting the results of a detailed analysis on the factors impacting the power consumption and performance of MPSoCs. In turn, the second part highlights the real-time implementation of fuzzy-logic-based power-efficient reconfigurable multi-core architectures for Intel and Leone3 processors.

General

Imprint: Springer Verlag, Singapore
Country of origin: Singapore
Series: SpringerBriefs in Computational Intelligence
Release date: November 2016
First published: 2017
Authors: Jameel Ahmed • Mohammed Yakoob Siyal • Shaheryar Najam • Zohaib Najam
Dimensions: 235 x 155 x 4mm (L x W x T)
Format: Paperback
Pages: 62
Edition: 1st ed. 2017
ISBN-13: 978-981-10-3119-9
Categories: Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Circuits & components
Books > Computing & IT > Computer hardware & operating systems > Computer architecture & logic design > General
Books > Computing & IT > Applications of computing > Artificial intelligence > Neural networks
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LSN: 981-10-3119-3
Barcode: 9789811031199

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