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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/80991完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 張建成(Chien-Cheng Chang) | |
| dc.contributor.author | Jin Lin | en |
| dc.contributor.author | 林瑨 | zh_TW |
| dc.date.accessioned | 2022-11-24T03:25:09Z | - |
| dc.date.available | 2021-09-11 | |
| dc.date.available | 2022-11-24T03:25:09Z | - |
| dc.date.copyright | 2021-09-11 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-09-06 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/80991 | - |
| dc.description.abstract | CZTSe硒化銅錫鋅為研究中的新型化合物太陽能電池材料，該材料具有低汙染、低製程成本的優勢，是取代目前太陽能電池材料的理想方案。製備薄膜硒化銅鋅錫時，材料形成的晶格結構會影響太陽能電池的光電特性，因此，進一步研究硒化銅鋅錫的結構對於理解及合理設計太陽能電池設備非常重要。本研究實作應用於計算硒化銅鋅錫中子衍射強度的蒙地卡羅演算法，透過演算法隨機生成硒化銅鋅錫的結構並根據薛丁格方程式計算其中子衍射強度，達到對實驗材料晶格結構精算的目的。為模擬實驗製備的粉末材料，演算法必須對龐大的晶格結構進行運算，以單核心CPU的運算能力進行需要耗費大量的時間來完成，而演算法的隨機性質需要多次的迭代計算來尋找最佳解，因此本研究針對演算法的效率進行研究以及優化。本研究以平行運算架構加速模擬運算效率，並透過增加硬體設備、提高並行性以及演算法優化等等方式提升模擬計算的效能，使硒化銅鋅錫中子衍射模擬演算法具擁有極高的效率。 本研究首先使用單個圖形處理器處理演算法中耗時最多的內積運算，以Nvidia公司提供的統一計算架構（CUDA）作為應用程式介面平行化演算法的計算，成功獲得5516倍的效能優化（相較於CPU）。隨後本研究更進一步使用訊息傳遞介面(MPI)將演算法分配至不同的核心進行運算，並啟用多個圖形處理器提高演算法的並行性；接著以不同的方式嘗試優化經過平行化的演算法，最佳化的使用各個硬體中的資源，使演算法能夠在對短的時間內完成。 最終本研究最佳化硒化銅鋅錫演算法，使模擬效能進一步提升至42678倍 (相較於CPU)，大幅提升演算法的效率。此外，本研究透過擴充數個功能提高演算法的可靠度，包括添加數值演算法—模擬退火(Simulated annealing)法，使演算法能夠在龐大的解空間中有規則的尋找全域最佳解；實作物件導向版本的演算法，增加程式的可讀性以及安全性。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-24T03:25:09Z (GMT). No. of bitstreams: 1 U0001-0209202115352000.pdf: 5164253 bytes, checksum: 84b7fc0a46a8189e1bcb2d36cb83b748 (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | 口試委員審定書 i 致謝 ii 摘要 iii Abstract iv 目錄 vi 圖目錄 viii 表目錄 x 第一章 緒論 1 1.1 前言 1 1.2 CZTSe硒化銅鋅錫 2 1.3 衍射 3 1.4 Reverse Monte Carlo 5 1.5 Simulated Annealing 6 1.6 Compute Unified Device Architecture 6 第二章 理論介紹 9 2.1 廣義的薛丁格方程式 9 2.2 定態薛丁格方程式 11 2.3 動量空間 12 2.4 玻恩定則 13 2.5 中子彈性衍射 13 第三章 模擬環境 15 3.1 中央處理單元 15 3.1.1 記憶體 16 3.1.2 CPU位元數 18 3.1.3 核心數量 19 3.1.4 工作時脈 21 3.2 圖形處理器 21 3.2.1 硬體架構 21 3.2.2 統一計算架構 28 3.3 應用程式介面 31 3.3.1 C語言 31 3.3.2 C++ 32 3.3.3 訊息傳遞介面（Message passing interface） 32 第四章 演算法介紹 35 4.1 逆向蒙地卡羅方法 35 4.2 模擬退火演算法 37 第五章 結果與討論 39 5.1 演算法架構 39 5.2 演算法優化 47 5.2.1 模擬晶格結構尺寸 47 5.2.2 圖形處理器運用 51 5.2.3 內核結構優化 54 5.2.4 MPI與多圖形處理器優化 57 5.2.5 平均計算量優化 60 5.2.6 非同步運算優化 62 5.2.7 循環展開優化 64 5.2.8 鎖定內存優化 66 5.2.9 程式語言模板化 67 5.3 模擬結果與誤差分析 69 5.4 結論 76 第六章 未來展望 77 第七章 參考文獻 79 | |
| dc.language.iso | zh-TW | |
| dc.subject | 中子衍射 | zh_TW |
| dc.subject | 平行運算 | zh_TW |
| dc.subject | CUDA | zh_TW |
| dc.subject | 硒化銅鋅錫 | zh_TW |
| dc.subject | 模擬退火法 | zh_TW |
| dc.subject | RMC演算法 | zh_TW |
| dc.subject | neutron diffraction | en |
| dc.subject | RMC algorithm | en |
| dc.subject | high performance computing | en |
| dc.subject | simulated annealing | en |
| dc.subject | CZTSe | en |
| dc.subject | CUDA | en |
| dc.title | 硒化銅鋅錫中子衍射模擬演算法開發及優化 | zh_TW |
| dc.title | Development and Optimization of CZTSe Neutron Scattering Simulation Algorithm | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 包淳偉(Chun-Wei Pao) | |
| dc.contributor.oralexamcommittee | 林真真(Hsin-Tsai Liu),牛仰堯(Chih-Yang Tseng),張家歐 | |
| dc.subject.keyword | 硒化銅鋅錫,中子衍射,RMC演算法,模擬退火法,平行運算,CUDA, | zh_TW |
| dc.subject.keyword | CZTSe,neutron diffraction,RMC algorithm,simulated annealing,high performance computing,CUDA, | en |
| dc.relation.page | 83 | |
| dc.identifier.doi | 10.6342/NTU202102958 | |
| dc.rights.note | 同意授權(限校園內公開) | |
| dc.date.accepted | 2021-09-07 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 應用力學研究所 | zh_TW |
| 顯示於系所單位： | 應用力學研究所 | |
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