Static scheduling of synchronous data flow programs for digital signal processing
IEEE Transactions on Computers
Embedded Multiprocessors: Scheduling and Synchronization
Embedded Multiprocessors: Scheduling and Synchronization
Experimental analysis of the fastest optimum cycle ratio and mean algorithms
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Schedulability analysis of applications with stochastic task execution times
ACM Transactions on Embedded Computing Systems (TECS)
Combining simulation and formal methods for system-level performance analysis
Proceedings of the conference on Design, automation and test in Europe: Proceedings
Proceedings of the 43rd annual Design Automation Conference
ACSD '06 Proceedings of the Sixth International Conference on Application of Concurrency to System Design
Throughput Analysis of Synchronous Data Flow Graphs
ACSD '06 Proceedings of the Sixth International Conference on Application of Concurrency to System Design
Global Analysis of Resource Arbitration for MPSoC
DSD '06 Proceedings of the 9th EUROMICRO Conference on Digital System Design
Efficient computation of buffer capacities for multi-rate real-time systems with back-pressure
CODES+ISSS '06 Proceedings of the 4th international conference on Hardware/software codesign and system synthesis
Software/Hardware Engineering with the Parallel Object-Oriented Specification Language
MEMOCODE '07 Proceedings of the 5th IEEE/ACM International Conference on Formal Methods and Models for Codesign
Journal of Systems Architecture: the EUROMICRO Journal
Iterative probabilistic performance prediction for multi-application multiprocessor systems
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Auto-design systematic methodology of cluster MPSoC for multiple concurrent applications
International Journal of Computer Applications in Technology
Hi-index | 0.00 |
The number of features that are supported in modern multimedia devices is increasing faster than ever. Estimating the performance of such applications when they are running on shared resources is becoming increasingly complex. Simulation of all possible use-cases is very time-consuming and often undesirable. In this paper, a new technique is proposed based on probabilistically estimating the performance of concurrently executing applications that share resources. Two different methods of employing this approach are presented and compared with state-of-the-art technique, and with achieved performance found through extensive simulations. The results are within 15% of simulation result (considered as reference case) and up to ten times better than a worst-case estimation approach. The approach scales very well with increasing number of applications, and can also be applied at run-time for admission control.