Energy-Aware Real-Time Task Scheduling on Local/Shared Memory Systems
17.06.2019
The rapid development of the Real-Time and Embedded System
(RTES) has increased the requirement on the processing capabilities of
sensors, mobile phones and smart devices, etc. Meanwhile, energy
efficiency techniques are in desperate need as most devices in RTES are
battery powered. Following the above two trends, this work explores the
memory system energy efficiency for a general multi-core architecture.
This architecture integrates a local memory in each processing core,
with a large off-chip memory shared among multiple cores. Decisions need
to be made on whether tasks will be executed with the shared memory or
the local memory to minimize the total energy consumption within
real-time constraints. This paper proposes optimal schemes as well as a
polynomial-time approximation algorithm with constant ratio.
Bio: Minming Li is currently an associate professor in the Department of
Computer Science, City University of Hong Kong. He received his Ph. D.
and B.E. degree in the Department of Computer Science and Technology at
Tsinghua University in 2006 and 2002 respectively. His research
interests include algorithmic game theory, combinatorial optimization
and algorithm design and analysis for scheduling problems.