Many-to-one network on chip application task mapping using genetic algorithm / Sarah Muhammad Rashad Taha Farag Khater ; Supervised Magda B. Fayek , Ahmed A. Morgan
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TextLanguage: English Publication details: Cairo : Sarah Muhammad Rashad Taha Farag Khater , 2015Description: 66 P. : charts ; 30cmOther title: - توزيع مهام التطبيقات على موارد شبكات الرقاقة بطريقة الكثير إلى الواحد باستخدام الخوارزمية الجينية [Added title page title]
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قاعة الرسائل الجامعية - الدور الاول | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.13.06.M.Sc.2015.Sa.M (Browse shelf(Opens below)) | Not for loan | 01010110068110000 | ||
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مخـــزن الرســائل الجـــامعية - البدروم | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.13.06.M.Sc.2015.Sa.M (Browse shelf(Opens below)) | 68110.CD | Not for loan | 01020110068110000 |
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| Cai01.13.06.M.Sc.2015.Os.E Enhancing intelligent agents by improving human behavior imitation using statistical modeling techniques / | Cai01.13.06.M.Sc.2015.Os.E Enhancing intelligent agents by improving human behavior imitation using statistical modeling techniques / | Cai01.13.06.M.Sc.2015.Sa.M Many-to-one network on chip application task mapping using genetic algorithm / | Cai01.13.06.M.Sc.2015.Sa.M Many-to-one network on chip application task mapping using genetic algorithm / | Cai01.13.06.M.Sc.2015.Sh.P A priority multi-channel coordination mac protocol in vehicular networks / | Cai01.13.06.M.Sc.2015.Sh.P A priority multi-channel coordination mac protocol in vehicular networks / | Cai01.13.06.M.Sc.2015.Wa.M Multi-domain hierarchical recognition of complex sketches using topological and syntactical information / |
Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Computer Engineering
In 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
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