發(fā)布時(shí)間：2018-06-08 00:31

  本文選題：可配置處理器 + 傳輸觸發(fā)體系結(jié)構(gòu)(TTA)��； 參考：《天津大學(xué)》2012年碩士論文

【摘要】：隨著集成電路制造技術(shù)的進(jìn)步,各種可定制處理器在嵌入式設(shè)計(jì)中得到了廣泛的應(yīng)用。針對不同目標(biāo)處理器結(jié)構(gòu)生成優(yōu)化的代碼成了編譯器的一個(gè)艱巨而重要的工作。當(dāng)前,一種新型的可定制處理器結(jié)構(gòu)——傳輸觸發(fā)架構(gòu)(Transport Trigger Architecture, TTA)由于其靈活性、可擴(kuò)展、高性能、低成本和低功耗等特點(diǎn)在科研機(jī)構(gòu)和工業(yè)界中獲得了廣泛的關(guān)注。本文主要研究了TTA處理器的編譯器后端優(yōu)化部分,主要包括了指令篩選和指令調(diào)度。 本文采用圖變換的方式進(jìn)行DAG的預(yù)處理,解決了通常模式匹配中出現(xiàn)的由于拓?fù)浣Y(jié)構(gòu)不同,無法完成匹配的問題。通過按照一些特定的規(guī)則,在進(jìn)行指令匹配之前進(jìn)行DAG變換,使得變換之后的DAG結(jié)構(gòu)與功能一一對應(yīng),從而使得功能相同的部分能夠完全完成匹配。并且通過特殊的建模方法,使得存在交集的待匹配節(jié)點(diǎn)集合也可以同時(shí)匹配。之后采用啟發(fā)式的遺傳算法搜索到近似的最優(yōu)解。 在完成指令篩選之后,本文提出了一種基本塊范圍內(nèi)的融合了遺傳算法和禁忌搜索的新型搜索算法模型。在確定了指令間的相互依賴關(guān)系以及資源約束后,通過在遺傳算法的架構(gòu)下進(jìn)行禁忌搜索近似最優(yōu)的指令調(diào)度方案來完成指令調(diào)度。實(shí)驗(yàn)結(jié)果表明與其他常規(guī)算法相比該算法不僅能夠產(chǎn)生較高質(zhì)量的并行代碼,還能更快的完成收斂。
[Abstract]:With the development of IC manufacturing technology, various customizable processors have been widely used in embedded design. Generating optimized code for different target processor architectures has become a difficult and important task for compilers. At present, a new customizable processor architecture, Transport trigger Architecture (TTA), has gained wide attention in scientific research institutions and industry because of its flexibility, scalability, high performance, low cost and low power consumption. In this paper, the compiler back-end optimization of TTA processor is studied, including instruction filtering and instruction scheduling. In this paper, the DAG is preprocessed by graph transformation, which solves the problem of different topology in common pattern matching. Unable to complete the matching problem. According to some specific rules, the DAG transformation is carried out before the instruction matching, so that the transformed DAG structure corresponds to the function one by one, so that the part with the same function can complete the matching completely. And through the special modeling method, the set of nodes to be matched with intersection can be matched at the same time. Then the heuristic genetic algorithm is used to search the approximate optimal solution. After the instruction selection is completed, a new search algorithm model combining genetic algorithm and Tabu search is proposed in this paper. After the interdependence between instructions and resource constraints are determined, instruction scheduling is accomplished by using Tabu search approach to approximate optimal instruction scheduling scheme under the framework of genetic algorithm (GA). Experimental results show that this algorithm can not only produce high quality parallel code, but also complete convergence faster than other conventional algorithms.
【學(xué)位授予單位】：天津大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號】：TP332

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本文編號：1993531