Paper Info
Title
A unified online directed acyclic graph flow manager for multicore schedulers
Abstract
Numerous Directed-Acyclic Graph (DAG) schedulers have been developed to improve the energy efficiency of various multi-core systems. However, the DAG monitoring modules proposed by these schedulers make a priori assumptions about the workload and relationship between the task dependencies. Thus, schedulers are limited to work on a limited subset of DAG models. To address this problem, we propose a unified online DAG monitoring solution independent from the connected scheduler and able to handle all possible DAG models. Our novel low-complexity solution processes online the DAG of the application and provides relevant information about each task that can be used by any scheduler connected to it. Using H.264/AVC video decoding as an illustrative application and multiple configurations of complex synthetic DAGs, we demonstrate that our solution connected to an external simple energy-efficient scheduler is able to achieve significant improvements in energy-efficiency and deadline miss rates compared to existing approaches.
Year
DOI
Venue
2014
10.1109/ASPDAC.2014.6742974
ASP-DAC
Keywords
Field
DocType
processor scheduling,power aware computing,unified online directed acyclic graph flow manager,dag schedulers,complex synthetic dags,task dependency,h.264/avc video decoding,video coding,low-complexity solution,directed graphs,dag monitoring modules,multicore scheduler system,external simple energy-efficient scheduler,decoding,parallel processing
Efficient energy use,Computer science,Workload,Flow (psychology),A priori and a posteriori,Directed graph,Real-time computing,Directed acyclic graph,Decoding methods,Multi-core processor,Distributed computing
Conference
ISSN
Citations 
PageRank 
2153-6961
1
0.36
References 
Authors
12
4
Name
Order
Citations
PageRank
Karim Kanoun1172.27
David Atienza22219149.60
Nicholas Mastronarde324026.93
Mihaela Van Der Schaar43968352.59