Analysis of systemc actor networks for efficient synthesis

Journal article
(Original article)


Publication Details

Author(s): Falk J, Zebelein C, Keinert J, Haubelt C, Teich J, Bhattacharyya SS
Journal: ACM Transactions on Embedded Computing Systems
Publisher: Association for Computing Machinery (ACM)
Publication year: 2010
Volume: 10
Journal issue: 2
ISSN: 1539-9087


Abstract


Applications in the signal processing domain are often modeled by dataflow graphs. Due to heterogeneous complexity requirements, these graphs contain both dynamic and static dataflow actors. In previous work, we presented a generalized clustering approach for these heterogeneous dataflow graphs in the presence of unbounded buffers. This clustering approach allows the application of static scheduling methodologies for static parts of an application during embedded software generation for multiprocessor systems. It systematically exploits the predictability and efficiency of the static dataflow model to obtain latency and throughput improvements. In this article, we present a generalization of this clustering technique to dataflow graphs with bounded buffers, therefore enabling synthesis for embedded systems without dynamic memory allocation. Furthermore, a case study is given to demonstrate the performance benefits of the approach. © 2010 ACM.



FAU Authors / FAU Editors

Falk, Joachim
Lehrstuhl für Informatik 12 (Hardware-Software-Co-Design)
Haubelt, Christian Prof. Dr.-Ing.
Technische Fakultät
Teich, Jürgen Prof. Dr.-Ing.
Lehrstuhl für Informatik 12 (Hardware-Software-Co-Design)


How to cite

APA:
Falk, J., Zebelein, C., Keinert, J., Haubelt, C., Teich, J., & Bhattacharyya, S.S. (2010). Analysis of systemc actor networks for efficient synthesis. ACM Transactions on Embedded Computing Systems, 10(2). https://dx.doi.org/10.1145/1880050.1880054

MLA:
Falk, Joachim, et al. "Analysis of systemc actor networks for efficient synthesis." ACM Transactions on Embedded Computing Systems 10.2 (2010).

BibTeX: 

Last updated on 2018-19-04 at 03:25