以多核心系統架構為基礎在可程式化系統晶片中實現島嶼式基因演算法
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2009
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Abstract
本研究為向量量化器的設計提出一個島嶼式(分散式)基因演算法的架構。研究中以多核心的系統架構為基礎,而為了獨立的基因演化過程,每一個島嶼分別都包含著一個硬體加速器以及一個softcore處理器。而島嶼之間的相互基因移民是採用一個共享的on-chip RAM,而這個on-chip RAM被一個硬體mutex給控制著以避免發生資料存取誤用。這樣為硬體實現分散式基因演算法提供了一個簡單以及具有彈性的移民機制。實驗數據顯示了我們所提出的硬體架構相對於其對應的軟體模擬系統擁有較低的計算時間。
This thesis presents a novel distributed genetic algorithm (GA) architecture for the design of vector quantizers. The design is based on a multi-core architecture, where each island of the GA is associated with a hardware accelerator and a softcore processor for independent genetic evolutions. An on-chip RAM with a mutex circuit is adopted for the migration of genetic strings among different islands. This allows a simple and flexible migration for the implementation of hardware distributed GA. Experimental results shows that the proposed architecture has significantly lower computational time as compared with its software counterparts for GA-based optimization.
This thesis presents a novel distributed genetic algorithm (GA) architecture for the design of vector quantizers. The design is based on a multi-core architecture, where each island of the GA is associated with a hardware accelerator and a softcore processor for independent genetic evolutions. An on-chip RAM with a mutex circuit is adopted for the migration of genetic strings among different islands. This allows a simple and flexible migration for the implementation of hardware distributed GA. Experimental results shows that the proposed architecture has significantly lower computational time as compared with its software counterparts for GA-based optimization.
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分散式基因法則, 系統晶片設計, 多核心系統, 向量量化器, Distributed GA, SOPC, Multi-core System, Vector Quantizers