CPU-GPU協(xié)同的Andorid平臺游戲功耗管理研究
發(fā)布時間：2018-09-12 06:06
【摘要】：當前移動智能終端設備數(shù)量增長迅猛,性能提升顯著,在滿足用戶需求的同時,凸顯了其固有的能耗與電池容量之間的矛盾。動態(tài)電壓頻率調(diào)節(jié)(DVFS)是能夠有效解決這種矛盾的一種機制。但是傳統(tǒng)策略中,處理器負載評估依賴底層硬件反饋、CPU和GPU功耗管理模塊完全獨立,無法充分利用不同類型應用的獨有特性進一步提高移動智能終端設備的能效。本文關注Android智能手機處理器功耗管理和能效提升。以"上層應用特性驅(qū)動的底層處理器功耗管理"思想為指引,選取Android移動平臺游戲應用為研究對象,探究游戲運行時行為特性和CPU-GPU負載特性,指導CPU-GPU協(xié)同功耗管理方案的設計與實現(xiàn)。具體來說,本文的主要工作包括:1.構建了針對Android平臺游戲應用的功耗管理框架�？蚣鼙苊鈱C平臺的過度借鑒,利用操作系統(tǒng)的應用管理和資源分配功能,縱向聯(lián)通應用層和底層處理器功耗管理模塊,使DVFS算法可以直接感知上層游戲計算需求變化;橫向聯(lián)通CPU和GPU相互獨立的功耗管理模塊,使二者可以相互感知對方進行協(xié)同管理�？蚣転榛谟螒蛱匦缘腃PU/GPU負載評估和CPU-GPU協(xié)同DVFS算法奠定基礎。2.提出用戶交互感知的CPU負載評估方法和基于游戲幀復雜度的GPU負載評估方法。方法利用Android游戲運行時的用戶交互特性,以用戶交互消息數(shù)評估CPU負載中的用戶交互部分;利用CPU-GPU之間的數(shù)據(jù)交互特性,在CPU處以游戲中頂點、紋理和命令數(shù)據(jù)提前評估GPU負載,解決了傳統(tǒng)基于硬件利用率反饋方法延遲高和準確度低的問題。3.設計了針對Android游戲的CPU-GPU協(xié)同DVFS算法。算法以保證用戶體驗為導向,對游戲用戶體驗、CPU-GPU負載構建了變化感知的協(xié)同描述,為電壓頻率調(diào)控指明時機和方向;協(xié)同調(diào)頻邏輯基于游戲運行時CPU-GPU之間功能上的生產(chǎn)者——消費者協(xié)作關系設計,做到"協(xié)同"而非"同時獨立"的CPU-GPU功耗管理。本文在ODROID-XU3實驗平臺上實現(xiàn)了上述工作。實驗評價中,本文以平均幀處理時間(性能)和平均幀能耗(能耗)的比值作為游戲運行時系統(tǒng)的能效量化值。實驗結果表明:相比傳統(tǒng)方法,本文方案在保證Android游戲用戶體驗前提下可以達到平均12%,最高34%的能效提升。
[Abstract]:At present, the number of mobile intelligent terminal devices is growing rapidly and the performance is improving significantly. While meeting the needs of users, it highlights the contradiction between its inherent energy consumption and battery capacity. Dynamic voltage frequency regulation (DVFS) is an effective mechanism to solve this contradiction. But in the traditional strategy, the processor load evaluation depends on the underlying hardware feedback CPU and GPU power management module completely independent, can not make full use of the unique characteristics of different types of applications to further improve the energy efficiency of mobile intelligent terminal devices. This paper focuses on Android smart phone processor power management and energy efficiency. Guided by the idea of "the power management of the bottom processor driven by the upper application characteristics", this paper selects the Android mobile platform game application as the research object, and probes into the game runtime behavior characteristics and the CPU-GPU load characteristics. To guide the design and implementation of CPU-GPU collaborative power management scheme. Specifically, the main work of this paper includes: 1. 1. A power management framework for Android platform game applications is constructed. The framework avoids the excessive reference to the PC platform and uses the application management and resource allocation functions of the operating system to connect the application layer and the underlying processor power management module vertically so that the DVFS algorithm can directly perceive the changes of the upper level game computing requirements. The power management module of CPU and GPU is independent of each other so that they can perceive each other and manage each other collaboratively. The framework lays the foundation for CPU/GPU load evaluation based on game features and CPU-GPU cooperative DVFS algorithm. 2. 2. The CPU load evaluation method based on user interaction awareness and the GPU load evaluation method based on game frame complexity are proposed. Methods the user interaction part of the CPU load was evaluated by the number of user interactive messages in the Android game run time, and the vertex of the CPU was determined by the data interaction property between the CPU-GPU. Texture and command data are used to evaluate GPU load in advance, which solves the problem of high delay and low accuracy based on traditional feedback method of hardware utilization. A CPU-GPU cooperative DVFS algorithm for Android games is designed. Under the guidance of ensuring user experience, the algorithm constructs a cooperative description of change perception for CPU-GPU load of game user experience, which indicates the timing and direction of voltage frequency regulation. The cooperative frequency modulation logic is based on the producer-consumer cooperative relationship between the CPU-GPU when the game is running, and achieves "collaborative" rather than "simultaneous independent" CPU-GPU power management. In this paper, the above work is realized on the ODROID-XU3 experimental platform. In the experimental evaluation, the ratio of average frame processing time (performance) and average frame energy consumption (energy consumption) is used as the energy efficiency quantization value of the game runtime system. The experimental results show that: compared with the traditional method, this scheme can achieve an average of 12 and a maximum of 34% energy efficiency improvement under the premise of guaranteeing the Android game user experience.
【學位授予單位】：中國科學技術大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP311.52;TP316
本文編號：2238130
[Abstract]:At present, the number of mobile intelligent terminal devices is growing rapidly and the performance is improving significantly. While meeting the needs of users, it highlights the contradiction between its inherent energy consumption and battery capacity. Dynamic voltage frequency regulation (DVFS) is an effective mechanism to solve this contradiction. But in the traditional strategy, the processor load evaluation depends on the underlying hardware feedback CPU and GPU power management module completely independent, can not make full use of the unique characteristics of different types of applications to further improve the energy efficiency of mobile intelligent terminal devices. This paper focuses on Android smart phone processor power management and energy efficiency. Guided by the idea of "the power management of the bottom processor driven by the upper application characteristics", this paper selects the Android mobile platform game application as the research object, and probes into the game runtime behavior characteristics and the CPU-GPU load characteristics. To guide the design and implementation of CPU-GPU collaborative power management scheme. Specifically, the main work of this paper includes: 1. 1. A power management framework for Android platform game applications is constructed. The framework avoids the excessive reference to the PC platform and uses the application management and resource allocation functions of the operating system to connect the application layer and the underlying processor power management module vertically so that the DVFS algorithm can directly perceive the changes of the upper level game computing requirements. The power management module of CPU and GPU is independent of each other so that they can perceive each other and manage each other collaboratively. The framework lays the foundation for CPU/GPU load evaluation based on game features and CPU-GPU cooperative DVFS algorithm. 2. 2. The CPU load evaluation method based on user interaction awareness and the GPU load evaluation method based on game frame complexity are proposed. Methods the user interaction part of the CPU load was evaluated by the number of user interactive messages in the Android game run time, and the vertex of the CPU was determined by the data interaction property between the CPU-GPU. Texture and command data are used to evaluate GPU load in advance, which solves the problem of high delay and low accuracy based on traditional feedback method of hardware utilization. A CPU-GPU cooperative DVFS algorithm for Android games is designed. Under the guidance of ensuring user experience, the algorithm constructs a cooperative description of change perception for CPU-GPU load of game user experience, which indicates the timing and direction of voltage frequency regulation. The cooperative frequency modulation logic is based on the producer-consumer cooperative relationship between the CPU-GPU when the game is running, and achieves "collaborative" rather than "simultaneous independent" CPU-GPU power management. In this paper, the above work is realized on the ODROID-XU3 experimental platform. In the experimental evaluation, the ratio of average frame processing time (performance) and average frame energy consumption (energy consumption) is used as the energy efficiency quantization value of the game runtime system. The experimental results show that: compared with the traditional method, this scheme can achieve an average of 12 and a maximum of 34% energy efficiency improvement under the premise of guaranteeing the Android game user experience.
【學位授予單位】：中國科學技術大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP311.52;TP316
【參考文獻】
相關期刊論文 前1條
1 帖軍;陳幼均;;進程同步中的生產(chǎn)者—消費者模型分析[J];武漢科技學院學報;2007年04期
，本文編號：2238130
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