A QoS-aware Dynamic Power Optimization for Data-Parallel JavaScript Programs

JavaScript has become a general-purpose programming environment that enables complex, media-rich web applications. An increasing number of JavaScript programs are parallelized to run efficiently on today’s multicore CPUs, which are capable of dynamic core scaling (DCS) and voltage/frequency scaling (DVFS). However, significant power savings are still left unrealized since an operating point (in terms of the number of active cores and CPU voltage/frequency) is selected by monitoring CPU utilization or OS events, without considering the user’s performance goal. To address this, we propose QPR.js, a QoS-aware power-optimizing runtime system for JavaScript. Using the QPR.js API, the application developer can specify an QoS constraint and provide a fitness function to quantify the current level of optimality. During execution the QPR.js runtime system uses this information to autonomously find an optimal operating point while satisfying this QoS constraint. Our evaluation demonstrates the effectiveness of QPR.js in finding optimal operating points while satisfying QoS constraints for three different optimization goals.