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研究生:簡士承
研究生(外文):Shih-Cheng Chien
論文名稱:適用於交通感知晶片網路系統之動態可調式路由引擎設計
論文名稱(外文):Dynamically Adjustable Routing Engine Design for Traffic-aware On-Chip Networking Systems
指導教授:吳安宇吳安宇引用關係
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:電子工程學研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2006
畢業學年度:95
語文別:英文
論文頁數:73
中文關鍵詞:交通感知晶片網路可調路由設計
外文關鍵詞:trafficawarechipnetworkadjustablerouterrouting enginedesign
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根據 International Technology Roadmap for Semiconductors (ITRS)所指出,晶片內系統的連線複雜度問題已經日趨嚴重並影響整個晶片內系統的效能。在近十年之後,現今較常被使用的晶片內匯流排傳輸機制將會在深次微米的環境中遇到瓶頸。有鑑於此,在最近幾年中晶片網路的研究被熱烈的討論,以解決晶片內匯流排所遇到的問題。
在本論文中,我們提出了晶片網路系統的設計概念,我們把以此
概念所設計出的晶片網路系統稱做交通感知晶片網路系統。此交通感知晶片網路系統必須是針對已知的交通流量提高硬體的效能(hardware efficiency),並且對未知的交通流量在線上做動態的調整以提高系統整體的效能。
針對硬體效能的問題,我們在硬體資料庫中建立不同種類的路由引擎並且建立一套節省硬體成本的流程。在已知的交通流量中,可以在網路的每個結點上選用最適合的路由引擎。本論文中所提出的可動態調整緩衝配置(dynamically adjustable buffer allocation)可以增加緩衝區的使用率,因此在達到同樣效能的基準下,只需要花費較少的硬體成本。
對於網路系統內不可預測的交通流量,所提出的交通感知排程
(traffic-aware scheduling)可降低擁塞發生率(congestion rate),提高頻寬的使用率(bandwidth utilization),進而降低封包延遲時間(packet latency),提高系統的總流量(system throughput)。經由暫存器傳輸等級(RTL)模擬得知,所提出的交通感知晶片網路系統比一般晶片網路系統能達到更好的效能,而其硬體成本僅比一般晶片內網路系統多約6.9%。
According to International Technology Roadmap for Semiconductors (ITRS), the interconnection complexity has increased and dominated the SoC design and its performance. By the end of the decade, the popular bus-based SoC communication will meet its bottleneck in the deep-submicron environment. Recently, researches on On-Chip Network (OCN) have been actively discussed to solve the problem of on chip bus.
In this thesis, we proposed a design concept of On-Chip Networking system (OCN system). The OCN system designed according to this concept is called traffic-aware OCN system. The traffic-aware OCN system should be hardware-efficient in already known traffic case and can dynamically adjust for better system performance at run time.
For hardware efficiency issue, we have built a variety of routing engines in the HW library and formed a hardware reduction flow. According to the already known traffic on the chip, we can choose the most suitable routing engine at each node of the network. The proposed dynamically adjustable buffer allocation can increase the buffer utilization and therefore can reach the same performance with less hardware overhead.
For better system performance under unpredictable traffic, the proposed traffic-aware scheduling can lower the packet latency and increase system throughput by reducing congestion rate and increasing bandwidth utilization. The RTL simulation shows the OCN system with traffic-aware scheduling performs better than the generic OCN system under uniform random traffic and hotspot traffic. The hardware overhead of traffic-aware technique is merely 6.9%.
Abstract xviii
Contents xx
List of Figures xxii
Chapter 1 Introduction 1
Chapter 2 Routing Engine Architecture 9
2.1 Basic Routing Engine Architecture 9
2.1.1 Separate Buffer Routing Engine 12
2.1.2 Central Buffer Routing Engine 16
2.1.3 Feature Comparison 20
2.2 Hardware Efficiency Optimization 22
2.2.1 Traffic Surface and Bandwidth Surface 22
2.2.2 Hardware Efficiency Optimization Flow 23
Chapter 3 Proposed Dynamically Adjustable Buffer Allocation 29
3.1 Buffer Utilization Issue 29
3.2 Dynamically Adjustable Buffer Allocation 30
3.2.1 Conventional Circular Buffer Approach 31
3.2.2 Proposed Simplified Linked List Approach 32
3.2.3 Hardware Overhead & Performance Analysis 34
Chapter 4 Proposed Run-Time Traffic-Aware Scheduling 37
4.1 Traffic-Aware Scheduling Algorithm & Mechanism 37
4.2 Realization of Traffic-aware Scheduling 39
4.2.1 Traffic-aware Marker 40
4.2.2 Traffic-aware Arbiter 41
4.2.3 Hardware Overhead & Performance Analysis 42
Chapter 5 OCN system Performance and Analysis 45
5.1 Traffic Configuration 45
5.2 Performance Metrics 48
5.3 Performance Analysis of Dynamically Adjustable Buffer Allocation 51
5.3.1 3x3 mesh network under uniform random traffic 52
5.3.2 4x4 mesh network under VOPD application traffic 55
5.4 Performance Analysis of Traffic-aware Scheduling 58
5.4.1 4x4 mesh network under uniform random traffic 59
5.4.2 4x4 mesh network under hotspot traffic 63
Chapter 6 Conclusion 67
6.1 Summary 67
6.2 Future Works 69
References 71
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