本文關(guān)鍵詞： clang SIMD 代碼轉(zhuǎn)換 領(lǐng)域編程語言 編譯工具　出處：《吉林大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著現(xiàn)代社會的計算機技術(shù)高速發(fā)展,對計算機高性能計算能力也提出了更高的需求,尤其在特定的多媒體圖像與無線通訊領(lǐng)域的研發(fā)場景中,需要大量密集型的數(shù)據(jù)運算操作,傳統(tǒng)數(shù)據(jù)串行處理方法難以達到理想效果,在CPU物理性能達到瓶頸的情況下,CPU的主流處理方法則是進行SIMD(單指令多數(shù)據(jù))操作,其使用SIMD寄存器完成數(shù)據(jù)并行處理來取得加速收益。同時,隨著編譯器技術(shù)的不斷發(fā)展,領(lǐng)域?qū)＜姨岢霾崿F(xiàn)了通過相關(guān)編譯器自動生成高性能代碼的解決方案,因此,完整的SIMD代碼自動化轉(zhuǎn)換技術(shù)在程序生產(chǎn)環(huán)境中存在實際意義,其可以縮短研發(fā)周期,降低人力成本,同時保證SIMD程序的準(zhǔn)確性并進行相關(guān)程序優(yōu)化。本文中和特定領(lǐng)域算法特征,基于clang編譯器擴展了一套自定義高層語言SIMC到SIMD程序自動轉(zhuǎn)換工具。其中SIMC是一種面向圖像與無線通訊領(lǐng)域擴展的類C程序語言,SIMC進行了一些語言擴展,例如加入矩陣、向量、復(fù)數(shù)等關(guān)鍵字,其能夠完整描述應(yīng)用特征;同時還擴展了對算子表達式的描述(如矩陣卷積、矩陣和運算表達式)。作為編譯器輸入語言SIMC可以提升開發(fā)效率,降低程序優(yōu)化成本與算法復(fù)雜度。經(jīng)過編譯之后,可自動生成針對特定硬件平臺的SIMD程序。SIMC到SIMD的編譯轉(zhuǎn)換工具主要工作集中在clang編譯器的擴展開發(fā),在編譯器的詞法、語法、語義分析過程中,本文通過對SIMC程序的特定關(guān)鍵字和算子表達式進行并行性分析,在中間表示AST上進行針對特殊表達式的節(jié)點變換,其為代碼轉(zhuǎn)換工具的核心工作。其中具體實現(xiàn)設(shè)計可分為對特定表達式的擴展及其轉(zhuǎn)換接口設(shè)計,變量基礎(chǔ)信息收集,循環(huán)迭代區(qū)間并行性分析,調(diào)用SIMD內(nèi)置函數(shù)接口設(shè)計,本論文框架分別介紹了SIMC語言設(shè)計說明及其算法特征,SIMD操作原理,clang編譯器及其擴展原理,代碼并行性分析及其實現(xiàn)模塊設(shè)計。最后一步,對特定算法的SIMC程序自動轉(zhuǎn)換生成的SIMD代碼進行正確性與性能驗證,通過對比其程序性能與專家手工優(yōu)化版本相一致,最終測試數(shù)據(jù)表明,在X86平臺上SIMC-SIMD編譯轉(zhuǎn)換工具可以將程序時間運行效率較之串行語言提高3.85-6.59倍。
[Abstract]:With the rapid development of computer technology in modern society, there is a higher demand for high performance computing power of computer, especially in the research and development of specific multimedia image and wireless communication field. A large number of intensive data operations are required, so the traditional method of serial data processing is difficult to achieve ideal results. When the physical performance of CPU reaches the bottleneck, the mainstream processing method of CPU is to carry out single instruction multi-data operation. At the same time, with the continuous development of compiler technology, domain experts have proposed and implemented a solution to automatically generate high-performance code through related compilers. The complete SIMD code automation technology has practical significance in the program production environment, it can shorten the research and development cycle, reduce the labor cost, At the same time to ensure the accuracy of the SIMD program and related program optimization. Based on the clang compiler, this paper extends a set of automatic conversion tools from SIMC to SIMD program. SIMC is a C-like programming language for image and wireless communication, which extends some languages, such as adding matrix, vector, etc. It also extends the description of operator expressions (such as matrix convolution, matrix and operation expression). As a compiler input language, SIMC can improve the development efficiency. To reduce the cost of program optimization and algorithm complexity. After compiling, can automatically generate specific hardware platform specific SIMD program SIMC to SIMD compiler conversion tools mainly focus on the expansion of the clang compiler development, in the compiler lexical, syntax, In the process of semantic analysis, this paper analyzes the parallelism of the special keywords and operator expressions of SIMC programs, and transforms the nodes of special expressions on the intermediate representation AST. It is the core work of the code conversion tool, in which the concrete implementation design can be divided into the extension of a specific expression and its conversion interface design, variable basic information collection, cycle iteration interval parallelism analysis, calling SIMD built-in function interface design. The framework of this paper introduces the SIMC language design description and its algorithm characteristic, the principle of SIMD operation and its extension principle, the code parallelism analysis and its implementation module design. The correctness and performance of the SIMD code generated by the automatic transformation of the SIMC program of the specific algorithm are verified. The program performance is consistent with that of the expert manual optimization version. The final test data show that, On the X86 platform, the SIMC-SIMD compiler and conversion tool can improve the program time efficiency by 3.85-6.59 times compared with the serial language.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP314

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