Simultaneous multithreading: maximizing on-chip parallelism
ISCA '95 Proceedings of the 22nd annual international symposium on Computer architecture
Proceedings of the 6th international workshop on Hardware/software codesign
Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
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Modeling, Verification, and Exploration of Task-Level Concurrency of Real-Time Embedded Systems
Modeling, Verification, and Exploration of Task-Level Concurrency of Real-Time Embedded Systems
Computers and Intractability: A Guide to the Theory of NP-Completeness
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Managing dynamic concurrent tasks in embedded real-time multimedia systems
Proceedings of the 15th international symposium on System Synthesis
Low power system scheduling and synthesis
Proceedings of the 2001 IEEE/ACM international conference on Computer-aided design
Energy-Aware Runtime Scheduling for Embedded-Multiprocessor SOCs
IEEE Design & Test
The Spring Kernel: A New Paradigm for Real-Time Systems
IEEE Software
Resource Reclaiming in Multiprocessor Real-Time Systems
IEEE Transactions on Parallel and Distributed Systems
Profile-Based Dynamic Voltage Scheduling Using Program Checkpoints
Proceedings of the conference on Design, automation and test in Europe
On-Line Dynamic Voltage Scaling for Hard Real-Time Systems Using the EDF Algorithm
RTSS '04 Proceedings of the 25th IEEE International Real-Time Systems Symposium
Quasi-Static Voltage Scaling for Energy Minimization with Time Constraints
Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
QoS Control Strategies for High-Quality Video Processing
Real-Time Systems
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SAMOS '09 Proceedings of the 9th International Workshop on Embedded Computer Systems: Architectures, Modeling, and Simulation
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Today's embedded applications often consist of multiple concurrent tasks. These tasks are decomposed into sub-tasks which are in turn assigned and scheduled on multiple different processors to achieve the Pareto-optimal performance/energy combinations. Previous work introduced systematical approaches to make performance-energy trade-offs explorations for each individual task and used the exploration results at run-time to fulfill system-level constraints. However, they did not exploit the fact that the concurrent tasks can be executed in an overlapped fashion. In this paper, we propose a simple yet powerful on-line technique that performs task overlapping by run-time subtask re-scheduling. By doing so, a multiprocessor system with concurrent tasks can achieve better performance without extra energy consumption. We have applied our algorithm to a set of randomly-generated task graphs, obtaining encouraging improvements over non-overlapped task, and also having less overall energy consumption than a previous DVS method for real-time tasks. Then, we have demonstrated the algorithm on real-life video- and image-processing applications implemented on a dual-processor TI TMS320C6202 board: We have achieved a reduction of 22---29% in the application execution time, while the impact of run-time scheduling overhead proved to be negligible (1.55%).