1. Compositionality in Synchronous Data Flow
Stavros Tripakis
Dai Bui
Bert Rodiers
Edward A. Lee
Marc Geilen
Compositionality in Synchronous Data Flow
Context
Preliminary Implementation
Profile Synthesis
Model-based design for embedded software: build software starting from high-level models
Synchronous Data Flow (SDF): popular model in embedded systems, signal processing
Ptolemy II: heterogeneous modeling environment that includes hierarchical SDF models
Rate Analysis
Deadlock Analysis
Hierarchical SDF Graphs
Test Cases
Unfolding SDF Schedule Graph
Motivation: Incremental Compilation
Large Ptolemy models => long time to compile
Incremental compilation: generate code for parts of the model independently from others => modularity
Ongoing Work
Comparing clustering algorithms
Modular performance analysis
Refolding
Actor Firing Clustering
Problem: SDF is not Compositional
Abstracting composite SDF into atomic SDF can result to deadlocks during feedback
References
S. Tripakis, D. Bui, B. Rodiers, and E.A. Lee. Compositionality in Synchronous Data Flow: Modular Code Generation from Hi- erarchical SDF Graphs. Technical Report UCB/EECS , EECS Department, University of California, Berkeley, Oct 2009.
E.A. Lee and D.G. Messerschmitt. Static scheduling of synchronous data flow programs for digital signal processing. IEEE Trans. Comput., 36(1):24–35, 1987.
R. Lublinerman, C. Szegedy, and S. Tripakis. Modular code generation from synchronous block diagrams: modularity vs. code size. In Principles of Programming Languages – POPL’09, pages 78–89. ACM, January 2009.
J. Falk, J. Keinert, C. Haubelt, J. Teich, and S. Bhattacharyya. A generalized static data flow clustering algorithm for mpsoc scheduling of multimedia applications. In Embedded Software – EMSOFT’08, pages 189–198. ACM, 2008.
Greedy Backward Disjoint Clustering
Our Proposal: Non-Monolithic Profiles
Each actor has multiple different firing functions
April 13, 2010
Center for Hybrid and Embedded Software Systems