在多核心即時嵌入式系統下考量系統負載之高能源效率動態電壓調整排程演算法

Abstract

在多核心即時嵌入式系統中，記憶體是一個重要的共享資源。因為需要等待記憶體的需求被服務，核心之間互相競爭記憶體會使得總執行時間增長。在本篇論文中，我們研究在考量記憶體競爭下之多核心即時嵌入式系統的任務分割排班問題。在考慮各任務的記憶體工作量特性下，我們提出一個改善現有基於最大工作量任務優先方法(LTF-MES)之高能源效率排程演算法，叫做考量系統負載之高能源效率動態電壓調整排程演算法。而我們提出的演算法和最大工作量任務優先之演算法最大的不同在於，我們考慮任務的執行順序，可因此減少核心之間相互競爭記憶體的頻率。實驗結果顯示，藉由減少任務與任務之間互相競爭記憶體，可以增加寬裕時間。而且，我們的演算法可以利用這些寬裕時間來減少在擁有不同任務數量的多核心系統中所需的總執行時間和總能源消耗。在變動的工作數量以及核心數目在2到16個之間的環境中，使用本演算法相對於LTF，可以在沒有使用動態調整電壓的情況下，降低2 %到10.3 %的總執行時間，並且可以在有支援動態調整電壓的情況下，相對於LTF-MES，改善3.85%到19% 的總能源消耗。

Memory is an important shared resource in a multi-core real-time embedded system. The memory contentions between cores will lengthen the total execution time due to waiting for memory requests being served. In this thesis, we focus on the tasks partition scheduling problem while considering memory contentions in multi-core real-time embedded systems. We propose an energy efficient scheduling mechanism with consideration to the memory workload of tasks, called WAS-DVS (workload-aware scheduling-dynamic voltage scaling), which is an improvement of an existing method, LTF-MES (Largest-Task-First-Minimize-Energy-Scheduling). The main difference between ours and LTF-MES is that we consider the execution order of tasks that may reduce the frequency of memory contentions. Simulation results show that by reducing memory contentions between tasks, the slack time will increase and the proposed WAS-DVS can use it to lower total execution time and total energy consumption on a variety of workloads in multi-core systems. The proposed WAS-DVS can lower the total execution time from 2% to 10.3% before applying DVS and improve the total energy consumption from 3.85% to 19% compared to LTF-MES, under various numbers of tasks and 2 to 16 cores after applying DVS.