Demystifying the cost of task migration in distributed memory many-core systems

Task migration plays a major role in the implementation of runtime adaptive techniques for many-core systems, as thermal and power management, load balancing, QoS, and fault tolerance. A fast task migration protocol contributes to implementing self-adaptive techniques with low overhead. State-of-the-art proposals still have limitations, with an important impact on the applications' execution time due to the latency to migrate tasks. Aware of the number of simultaneous task migrations required by self-adaptive techniques, this work proposes a low latency tasks migration protocol for many-core systems with distributed memory hierarchy. Our technique eliminates checkpoints, task code replication, enables simultaneous task migrations even in tasks of the same application and parallelizes the task migration with the application execution. These features induce a low latency in the task migration, demystifying the cost to adopt task migration in distributed memory systems. Results compare the proposed approach to the related works.