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研究生: 蔡宗展
Tsai, Tsung-Chan
論文名稱: 用於晶片網路設計探索的特徵擷取流量產生器
Attackboard Plus: A Pattern-Driven Traffic Generator for NoC Design Space Exploration
指導教授: 金仲達
King, Chung-Ta
口試委員: 金仲達
King, Chung-Ta
黃婷婷
Hwang, TingTing
徐慰中
Hsu, Wei-Chung
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 資訊工程學系
Computer Science
論文出版年: 2012
畢業學年度: 100
語文別: 英文
論文頁數: 44
中文關鍵詞: 晶片網路流量產生器封包相依性
外文關鍵詞: NoC, Traffic generator, Packet dependency
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  • 隨著單一晶片上的核心數不斷地增加,晶片網路(Network-on-Chip)成為連結各核心的主要媒介;因此探索晶片網路的設計亦日漸重要。計算機結構研究者通常會建立一對應的模型以研究新的晶片網路架構,並根據其研究結果來實作。記錄導向的模擬為一常用的方式且適於快速地評估及探索新的晶片網路架構;但用來驅動模擬的記錄檔佔用了大量的儲存空間且難以透過網路來傳輸。藉由觀察這些記錄檔通常包含許多重複的特徵,一種基於區間特徵導向的流量產生器Attackboard在最近被提出來解決上述的問題。Attackboard的核心概念為建立記錄溝通特徵的表結構然後用以產生與原記錄檔相似的網路流量;然而Attackboard需要適當調校過的參數以達到可接受的準度,這樣的設計反而限制了其在晶片網路設計探索上的應用性。

    在此碩士論文中,我們提出了Attackboard Plus。我們透過新的考量流量相依性的二階表結構來產生晶片網路上的流量,改良了Attackboard的設計,並消除其所需的參數使產生的流量更符合原記錄檔。我們的評估結果顯示Attackboard Plus在只增加些微的儲存空間下達到更佳的準度;而實例研討的結果展示了Attackboard Plus的應用性及潛在的限制。


    As the number of cores in a chip increases continuously, Network-on-Chip (NoC) becomes the primary choice for interconnecting the cores. Exploring the design of NoC is hence important. To study a new NoC architecture, architects tend to establish an early-stage model of the interested architecture for evaluation and exploitation of the design space. The results are then used to guide the detailed implementation of the architecture. For fast evaluation and exploitation, trace-driven simulations are often preferred. The problem is that traces require huge space to store and are difficult to transport over the network. By observing that traces usually contain many repetitive, redundant communication patterns, a pattern-driven and interval-based traffic generator, Attackboard, was recently proposed. The idea is to build a small table of communication patterns that can be used to generate traffic to NoC on-the-fly during simulation, whereas the traffic is similar to that generated by the original trace. However, Attackboard requires well-tuned design parameters to obtain an acceptable accuracy compared with the original traces. This therefore limits the applicability of Attackboard.

    In this thesis, we propose Attackboard Plus, which uses a new two-level dependency-aware table to generate NoC traffic. It improves Attackboard by eliminating those design parameters and better matching the communication patterns in the original trace. Our evaluations show that Attackboard Plus achieves higher accuracy with slightly higher storage space overhead compared with Attackboard. Case studies on NoC design space exploration show the applicability of Attackboard Plus in general, though some limitations need to be observed.

    1 Introduction 1 2 Background 6 2.1 The Idea of Pattern-Driven Simulation . . . . . . . . . . . . . . . . . . . . . 6 2.2 Overview of Attackboard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.2.1 Packets Dependencies Extraction of Attackboard . . . . . . . . . . . 10 2.2.2 Simulation using Attackboard . . . . . . . . . . . . . . . . . . . . . . 11 2.3 Summary of Attackboard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.4 Problems of Attackboard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 3 Methodology 14 3.1 System Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.2 Structure of Attackboard Plus’s attackboard . . . . . . . . . . . . . . . . . . 16 3.3 Packets Dependencies Extraction . . . . . . . . . . . . . . . . . . . . . . . . 18 3.4 Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 4 Experimental Evaluation 26 4.1 Simulation Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 4.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 4.3 Evaluation Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 4.3.1 Storage Space Overhead . . . . . . . . . . . . . . . . . . . . . . . . . 28 4.3.2 Traffic Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 4.4 Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 4.4.1 NoC design space exploration . . . . . . . . . . . . . . . . . . . . . . 33 4.4.2 Parallel Object Detection . . . . . . . . . . . . . . . . . . . . . . . . 35 5 Conclusion 39

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