Static scheduling of synchronous data flow programs for digital signal processing
IEEE Transactions on Computers
Consistency in Dataflow Graphs
IEEE Transactions on Parallel and Distributed Systems
CODES '94 Proceedings of the 3rd international workshop on Hardware/software co-design
Throughput Analysis of Synchronous Data Flow Graphs
ACSD '06 Proceedings of the Sixth International Conference on Application of Concurrency to System Design
Liveness and Boundedness of Synchronous Data Flow Graphs
FMCAD '06 Proceedings of the Formal Methods in Computer Aided Design
Functional DIF for Rapid Prototyping
RSP '08 Proceedings of the 2008 The 19th IEEE/IFIP International Symposium on Rapid System Prototyping
Embedded Multiprocessors: Scheduling and Synchronization
Embedded Multiprocessors: Scheduling and Synchronization
Proceedings of the Conference on Design, Automation and Test in Europe
Worst-case performance analysis of synchronous dataflow scenarios
CODES/ISSS '10 Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Synchronous dataflow scenarios
ACM Transactions on Embedded Computing Systems (TECS)
Buffer capacity computation for throughput-constrained modal task graphs
ACM Transactions on Embedded Computing Systems (TECS)
Modeling adaptive streaming applications with parameterized polyhedral process networks
Proceedings of the 48th Design Automation Conference
Hierarchical finite state machines with multiple concurrency models
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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Wireless embedded applications have stringent temporal constraints. The frame arrival rate imposes a throughput requirement that must be satisfied. These applications are often dynamic and streaming in nature. The FSM-based Scenario-Aware Dataflow (FSM-SADF) model of computation (MoC) has been proposed to model such dynamic streaming applications. FSM-SADF splits a dynamic system into a set of static modes of operation, called scenarios. Each scenario is modeled by a Synchronous Dataflow (SDF) graph. The possible scenario transitions are specified by a finite-state machine (FSM). FSM-SADF allows a more accurate design-time analysis of dynamic streaming applications, capitalizing on the analysability of SDF. However, existing FSM-SADF analysis techniques assume 1) scenarios are self-timed bounded, for which strong-connectedness is a sufficient condition, and 2) inter-scenario synchronizations are only captured by initial tokens that are common between scenarios. These conditions are too restrictive for many real-life applications. In this paper, we lift these restrictive assumptions and introduce a generalized FSM-SADF analysis approach based on the max-plus linear systems theory. We present both exact and conservative worst-case throughput analysis techniques that have varying levels of accuracy and scalability. The analysis techniques are implemented in a publicly available dataflow analysis tool and experimentally evaluated with different wireless applications.