Application-specific buffer space allocation for networks-on-chip router design
Proceedings of the 2004 IEEE/ACM International conference on Computer-aided design
RTSS '06 Proceedings of the 27th IEEE International Real-Time Systems Symposium
Power provisioning for a warehouse-sized computer
Proceedings of the 34th annual international symposium on Computer architecture
Boolean satisfiability from theoretical hardness to practical success
Communications of the ACM - A Blind Person's Interaction with Technology
Network calculus: a theory of deterministic queuing systems for the internet
Network calculus: a theory of deterministic queuing systems for the internet
Improving platform-based system synthesis by satisfiability modulo theories solving
CODES/ISSS '10 Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Satisfiability modulo theories: introduction and applications
Communications of the ACM
Satisfiability Modulo Graph Theory for Task Mapping and Scheduling on Multiprocessor Systems
IEEE Transactions on Parallel and Distributed Systems
Symbolic system synthesis in the presence of stringent real-time constraints
Proceedings of the 48th Design Automation Conference
TACAS'10 Proceedings of the 16th international conference on Tools and Algorithms for the Construction and Analysis of Systems
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We study the problem of assigning speeds to resources serving distributed applications with delay, buffer and energy constraints. We argue that the considered problem does not have any straightforward solution due to the intricately related constraints. As a solution, we propose using Real-Time Calculus (RTC) to analyse the constraints and a SATisfiability solver to efficiently explore the design space. To this end, we develop an SMT solver by using the OpenSMT framework and the Modular Performance Analysis (MPA) toolbox. Two key enablers for this implementation are the analysis of incomplete models and generation of conflict clauses in RTC. The results on problem instances with very large decision spaces indicate that the proposed SMT solver performs very well in practice.