Determining the Order of Processor Transactions in StaticallyScheduled Multiprocessors
Journal of VLSI Signal Processing Systems
Proceedings of the 6th international workshop on Hardware/software codesign
Embedded Multiprocessors: Scheduling and Synchronization
Embedded Multiprocessors: Scheduling and Synchronization
IEEE Transactions on Parallel and Distributed Systems
A Comparison of Heuristics for Scheduling DAGs on Multiprocessors
Proceedings of the 8th International Symposium on Parallel Processing
Energy reduction techniques for multimedia applications with tolerance to deadline misses
Proceedings of the 40th annual Design Automation Conference
Contention-Conscious Transaction Ordering in Embedded Multiprocessors
ASAP '00 Proceedings of the IEEE International Conference on Application-Specific Systems, Architectures, and Processors
Probabilistic performance guarantee for real-time tasks with varying computation times
RTAS '95 Proceedings of the Real-Time Technology and Applications Symposium
A modular simulation framework for architectural exploration of on-chip interconnection networks
Proceedings of the 1st IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Fast Exploration of Bus-Based On-Chip Communication Architectures
CODES+ISSS '04 Proceedings of the international conference on Hardware/Software Codesign and System Synthesis: 2004
Hi-index | 0.00 |
This paper explores the problem of efficiently ordering interprocessor communication operations in both statically and dynamically-scheduled multiprocessors for iterative dataflow graphs with probabilistic execution times. In most digital signal processing applications, the throughput of the system is significantly affected by communication costs. We explicitly model these costs within an effective graph-theoretic analysis framework. We show that ordered transaction schedules can significantly outperform both self-timed schedules and dynamic schedules for moderate task execution time variability. As the task execution time variability increases, we show that first self-timed and then dynamic scheduling policies are preferred. We perform an extensive experimental comparison on both real and simulated benchmarks to gauge the effect of synchronization and communication overhead costs on these crossover points.