A Dynamic Power-Aware Partitioner with Real-Time Task Migration for Embedded Multicore Processors

A Dynamic Power-Aware Partitioner with Task Migration for Multicore Embedded Systems

Nowadays, a key design issue in embedded systems is how to reduce the power consumption, since batteries have a limited energy budget. For this purpose, several techniques such as Dynamic Voltage Scaling (DVS) or task migration can be used. DVS allows reducing power by selecting the optimal voltage supply, while task migration achieves this effect by balancing the workload among cores. This pap...

Power-aware scheduling with effective task migration for real-time multicore embedded systems

CPPM: a Comprehensive Power-aware Processor Manager for a Multicore System

The growing functionality of mobile devices explains increasing system performance requirements and the subsequent wide adoption of multicore processors. As mobile systems are battery powered, battery life largely limits these high performing multicore mobile devices. Developing an efficient power-aware processor manager for mobile multicore systems has received considerable attention. The conv...

Sarkar, Abhik. Predictable Task Migration Support and Static Task Partitioning for Scalable Multicore Real-time Systems. (under the Direction of Frank Mueller.) Predictable Task Migration Support and Static Task Partitioning for Scalable Multicore Real-time Systems

SARKAR, ABHIK. Predictable Task Migration Support and Static Task Partitioning for Scalable Multicore Real-Time Systems. (Under the direction of Frank Mueller.) Multicores are becoming ubiquitous, not only in general-purpose but also embedded computing. This trend is a reflection of contemporary embedded applications posing steadily increasing demands in processing power. On such platforms, pre...

EcoMobile: Energy-aware Real-time Framework for Multicore Mobile Systems

In this paper, we propose a design and development plan to build an energy-aware framework for multicore mobile systems which extends Android with two features it lacks: fine-grain power management functionality and real-time support. We also provide three novel energy-aware real-time multicore scheduling algorithms to reduce both dynamic and leakage power consumptions. These algorithms address...