隨著目前的科技越來越發達，在我們的日常生活中不論是做研究或工作還是
一般生活上，我們常常要藉助各種的電腦設備來協助我們處理一些我們經常會使
用到的資料，而且處理的資料種類和數量也越來越多，例如衛星成像的數據處理、
基因工程計算、全球氣候預報數據、大量資料即時處理等等，這些大量資料中某
些特定類別的資料除了要求其正確性之外也要求其即時性，也就是希望能夠在短
時間之內求出其正確的運算結果。
根據MIT Technology Review 在2010 年8 月所公佈的相關報導指出，大量資
料即時處理為其中一個新興領域，其中也包括資料搜尋的部份，而ㄧ般談到資料
搜尋時所想到的就是資料比對，根據我們所指定要尋找的關鍵字或關鍵資料，然
後利用一些比對演算法在來源的資料做搜尋比對，進而找出結果
本研究就是要利用目前新ㄧ代GPU 的平行運算為基礎架構，去實現平行化比
對演算法，來建構出可處理大量即時資料之服務，並與目前知名的搜尋軟體Apache
Solr 做測試比較，找出其差異性與相對效能，以及未來可能之應用。

With the current technology more and more developed, in our daily life, whether
doing research or work, we often use a variety of computer equipment to help us deal
with some of our frequently used data. And the type and quantity of data have become
more and more, such as satellite imaging data, genetic engineering, the global climate
forecasting data, and complex event processing, etc. Some certain types of the data
require both accuracy and timeliness. That is, we hope to look for some data in a shorter
time.
According to MIT Technology Review in August 2010 reported that the relevant
published, complex event processing becomes a new research, and it also includes in
the part of data search. Data search often means data comparing. Given
specified keywords or key information which we are looking for, we design a pattern
matching algorithm to find the results within a shorter time, or even real-time.
In our research, the purpose is to use the general-purpose GPU, NVIDIA Tesla
C2050, with parallel computing architecture to implement parallelism of the pattern
matching. Finally, we construct a service to handle a large number of real-time data. We
also make some performance tests and compare the results with the well-known
software “Apache Solr” to find the differences and the possible application in the future.

致謝.........................................................i
中文摘要.....................................................ii
英文摘要....................................................iii
1 序論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1
1.1 研究動機..............................................1
1.2 問題描述..............................................2
2 GPU 和CUDA 簡介..........................................4
2.1 NVIDIA GPU...........................................4
2.1.1 從GPU 到CUDA.....................................4
2.1.2 CUDA 開發..........................................4
2.1.3 CUDA 程式架構......................................5
2.2 CUDA Programming Model.................................7
2.2.1 Host 和device.........................................7
2.2.2 Kernel. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7
2.2.3 CUDA 程序流程簡介...................................9
2.3 CUDA Thread Hierarchy...................................10
2.4 GPU 計算單元................................................12
2.5 CUDA Memory Model..................................13
3 Wu-Manber 演算法簡介. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15
3.1 Wu-Manber. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15
3.2 Shift table.............................................15
3.3 Hash table............................................15
3.4 Prefix table............................................16
3.5 比對過程................................................16
4 Aho-Corasick 演算法簡介....................................20
4.1 Aho-Corasick............................................20
4.2 演算法說明.............................................20
4.3 函數定義...............................................22
5 Apache Solr 搜尋軟體簡介....................................24
5.1 Solr 介紹.............................................24
5.2 Solr 安裝與配置........................................25
5.3 Solr 搜尋機制..........................................26
5.4 Lucene 簡介.............................................27
5.4.1 Lucene Package 簡介..................................29
5.4.2 基礎class............................................30
5.4.3 進階搜索.............................................32
5.4.4 Lucene 索引文件結構..................................35
6 程式架構與實作............................................39
6.1 程式架構大綱..........................................39
6.2 演算法前置處理部份......................................41
6.2.1 Wu-Manber 前置處理..................................41
6.2.2 Aho-Corasick 前置處理...................................44
6.3 演算法搜尋部份........................................46
6.3.1 Wu-Manber 搜尋處理....................................46
6.3.2 Aho-Corasick 搜尋處理...................................50
7 測試與實驗結果分析........................................52
7.1 最小Pattern 長度對演算法效能影響.........................52
7.2 CUDA Block number 對演算法效能的影響.....................53
7.3 CPU 與GPU 效能比較....................................54
7.4 CUDA 程式與Solr 軟體比較...............................55
8 結論.......................................................57
參考文獻............................................................58

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