000			02264cam a2200337 a 4500
003			EG-GiCUC
005			20250223031439.0
008			160310s2015 ua d f m 000 0 eng d
040			_aEG-GiCUC _beng _cEG-GiCUC
041	0		_aeng
049			_aDeposite
097			_aM.Sc
099			_aCai01.13.06.M.Sc.2015.Sa.M
100	0		_aSarah Muhammad Rashad Taha Farag Khater
245	1	0	_aMany-to-one network on chip application task mapping using genetic algorithm / _cSarah Muhammad Rashad Taha Farag Khater ; Supervised Magda B. Fayek , Ahmed A. Morgan
246	1	5	_aتوزيع مهام التطبيقات على موارد شبكات الرقاقة بطريقة الكثير إلى الواحد باستخدام الخوارزمية الجينية
260			_aCairo : _bSarah Muhammad Rashad Taha Farag Khater , _c2015
300			_a66 P. : _bcharts ; _c30cm
502			_aThesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Computer Engineering
520			_aIn this study, we address the task mapping on Networks on Chip (NoC) based architectures. The study proposes a novel many-to-one task mapping methodology to replace the current one-to-one mapping methodology. Many- to-one task mapping is based on mapping more than one single task on a single processing unit in a NoC-based system. In this thesis, we implement many-to- one multi-objective mapping using Genetic Algorithm (GA). The objective function maximizes system reliability and minimizes both communication power consumption and average packet latency. The methodology is evaluated by comparing it with di{uFB00}erent one-to-one mapping techniques. We also developed a C++-based simulator to evaluate our methodology. Experimental results showed that our approach outperforms one-to-one NMap, Simulated Annealing(SA), Branch and Bound (BB) and GA mapping by 133%, 187%, 155%, and 158%, respectively
530			_aIssued also as CD
653		4	_aGenetic Algorithm (GA)
653		4	_alatency
653		4	_amany-to-one
700	0		_aAhmed Abdelfattah Morgan , _eSupervisor
700	0		_aMagda Bahaa Eldin Fayek , _eSupervisor
856			_uhttp://172.23.153.220/th.pdf
905			_aAml _eCataloger
905			_aNazla _eRevisor
942			_2ddc _cTH
999			_c55469 _d55469