CARAT: Context-aware runtime adaptive task migration for multi core architectures

摘要

Multi core architectures that are built to reap performance and energy efficiency benefits from the parallel execution of applications often employ runtime adaptive techniques in order to achieve, among others, load balancing, dynamic thermal management, and to enhance the reliability of a system. Typically, such runtime adaptation in the system level requires the ability to quickly and consistently migrate a task from one core to another. For distributed memory architectures, the policy for transferring the task context between source and destination cores is of vital importance to the performance and to the successful operation of the system. As its performance is negatively correlated with the communication overhead, energy consumption and the dissipated heat, task migration needs to be runtime adaptive to account for the system load, chip temperature, or battery capacity. This work presents a novel context-aware runtime adaptive task migration mechanism (CARAT) that reduces the task migration latency by 93.12%, 97.03% and 100% compared to three state-of-the-art mechanisms and allows to control the maximum migration delay and the performance overhead tradeoff at runtime. This novel mechanism is built on an in-depth analysis of the memory access behavior of several multi-media and robotic embedded-systems applications.