Name
Title | ||
|---|---|---|
Power minimization for parallel real-time systems with malleable jobs and homogeneous frequencies |
Abstract | ||
|---|---|---|
In this work, we investigate the potential benefit of parallelization for both meeting real-time constraints and minimizing power consumption. We consider malleable Gang scheduling of implicit-deadline sporadic tasks upon multiprocessors. By extending schedulability criteria for malleable jobs to DPM/DVFS-enabled multiprocessor platforms, we are able to derive an offline polynomial-time optimal processor/frequency-selection algorithm. Simulations of our algorithm on randomly generated task systems executing on platforms having up to 16 processing cores show that the theoretical power consumption is reduced by a factor of 36 compared to the optimal non-parallel approach. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/RTCSA.2014.6910538 | Embedded and Real-Time Computing Systems and Applications |
Keywords | Field | DocType |
parallel processing,power aware computing,power consumption,processor scheduling,real-time systems,DPM-DVFS-enabled multiprocessor platforms,homogeneous frequencies,implicit-deadline sporadic tasks,malleable gang scheduling,malleable jobs,optimal nonparallel approach,parallel real-time systems,power consumption minimization,power minimization,randomly generated task systems,real-time constraints,schedulability criteria,theoretical power consumption | Metrical task system,Homogeneous,Computer science,Parallel computing,Parallel processing,Gang scheduling,Real-time computing,Multiprocessing,Power consumption,Distributed computing,Power minimization | Conference |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antonio Paolillo | 1 | 31 | 6.79 |
| Joël Goossens | 2 | 666 | 49.22 |
| Pradeep M. Hettiarachchi | 3 | 1 | 0.35 |
| Nathan Fisher | 4 | 472 | 32.45 |