异步I/O连接算法的峰值功率建模

Peak Power Modeling for Join Algorithms with Asynchronous I/Os

峰值功率是影响数据中心能效的一个重要因素.本文提出一种功率感知数据库系统中连接算法的峰值功率估算方法,非运行时峰值功率的估算的挑战在于没有运行时的系统信息作为模型的输入.为克服估算困难,提出使用 CPU密集度作为 CPU功耗指示量,理论上分析了异步 I/O连接算法在峰值功率发生阶段的特性,通过模拟连接算法峰值功率发生阶段算法行为来估算该阶段最大 CPU密集度,通过 CPU密集度与 CPU功率的内在联系建立异步I/O连接算法的峰值功率预测模型.实验对数据库系统中采用异步 I/O机制的四个连接算法时模型准确性进行了验证,结果表明所提预测方法具有较好的预测准确性,平均相对误差低于 7%.

Peak power is a critical factor on the power consumption of a data center.This paper proposes a peak power estimation method to predict the peak power to join operations in DBMS.The challenge of non-runtime peak power estimationlies in that there is no runtime system information to use for model construction.To overcome this issue,this paper uses CPU-boundedness as the proxy of CPU power consumption and analyzes the characteristics of the peak power occurring stage of join algorithms with async I/O in theory.By simulating the behavior of this stage,we estimate the maximal CPU-boundedness of join algorithms.By examining the relationship between the CPU-boundedness and CPU power,the peak power models of join algorithms under different CPU execution frequency are hence constructed.Experiments validate the effectiveness of the proposed models on threetypical join algorithms in DBMS with async I/O techniques.Results showed that our proposed methods had good accuracy with the average relative error less than 7%.