Abstract
The integration of static parameters into Synchronous Dataflow (SDF) models enables the customization of an application functional and non-functional behaviours. However, these parameter values are generally set by the developer for a manual Design Space Exploration (DSE). Instead of a single value, moldable parameters accept a set of alternative values, representing all possible configurations of the application. The DSE is responsible for selecting the best parameter values to optimize a set of criteria such as latency, energy, or memory footprint. However, the DSE process explodes in complexity with the number of parameters and their possible values.
In this paper, we study an automated DSE algorithm exploring multiple configurations of a dataflow application. Our experiments show that: 1) Only limited sets of configurations lead to Pareto-optimal solutions in a multi-criteria optimization scenario. 2) How individual parameters impact on optimization criteria are determined accurately from a limited subset of design points. The approach was evaluated on three image processing applications having from hundreds to thousands configurations.
This work was supported by DARK-ERA (ANR-20-CE46-0001-01).
A. Honorat, T. Bourgoin and H. Miomandre—Equal contribution.
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Notes
- 1.
For the throughput, its reciprocal is considered so that it can be minimized.
- 2.
Code is available upon request. For SIFT, see a similar version here: https://github.com/preesm/preesm-apps/tree/master/SIFT.
References
Bhattacharyya, S.S., Murthy, P.K., Lee, E.A.: Software synthesis from dataflow graphs, vol. 360. Springer, NY (1996). https://doi.org/10.1007/978-1-4613-1389-2
Bilsen, G., Engels, M., Lauwereins, R., Peperstraete, J.: Cycle-static dataflow. IEEE Trans. Signal Process. 44(2), 397–408 (1996)
Bouakaz, A., Fradet, P., Girault, A.: A survey of parametric dataflow models of computation. ACM Trans. Des. Autom. Electron. Syst. 22(2), 1–25 (2017)
Castrillón, J.: Programming heterogeneous MPSoCs: tool flows to close the software productivity gap. Ph.D. thesis, RWTH Aachen University, Aachen (2013). Aachen, Techn. Hochsch., Diss., 2013
Castrillon, J., Leupers, R., Ascheid, G.: Maps: mapping concurrent dataflow applications to heterogeneous MPSoCs. IEEE Trans. Industr. Inf. 9(1), 527–545 (2013)
Desnos, K., Pelcat, M., Nezan, J., Aridhi, S.: Pre- and post-scheduling memory allocation strategies on MPSoCs. In: Proceedings of the 2013 Electronic System Level Synthesis Conference (ESLsyn), pp. 1–6 (2013)
Desnos, K., Pelcat, M., Nezan, J.F., Bhattacharyya, S., Aridhi, S.: PiMM: parameterized and interfaced dataflow meta-model for MPSoCs runtime reconfiguration. In: Embedded Computer Systems: Architectures, Modeling, and Simulation (SAMOS), pp. 41–48. IEEE (2013)
Ecker, W., Müller, W., Dömer, R.: Hardware-dependent software, pp. 1–13. Springer, Dordrecht (2009). https://doi.org/10.1007/978-1-4020-9436-1_1
Honorat, A., Desnos, K., Bhattacharyya, S.S., Nezan, J.F.: Scheduling of synchronous dataflow graphs with partially periodic real-time constraints. In: Real-Time Networks and Systems. Paris, France (2020)
Kang, S., Yang, H., Schor, L., Bacivarov, I., Ha, S., Thiele, L.: Multi-objective mapping optimization via problem decomposition for many-core systems. In: 2012 IEEE 10th Symposium on Embedded Systems for Real-time Multimedia, pp. 28–37 (2012)
Lee, E.A., Messerschmitt, D.G.: Synchronous data flow. Proc. IEEE 75(9), 1235–1245 (1987)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60(2), 91–110 (2004)
Pelcat, M., Desnos, K., Heulot, J., Guy, C., Nezan, J., Aridhi, S.: Preesm: a dataflow-based rapid prototyping framework for simplifying multicore DSP programming. In: 2014 6th European Embedded Design in Education and Research Conference (EDERC), pp. 36–40 (2014)
Schwarzer, T., et al.: Compilation of dataflow applications for multi-cores using adaptive multi-objective optimization. ACM Trans. Des. Autom. Electron. Syst. 24(3), 1–23 (2019)
Wang, J., Roop, P.S., Girault, A.: Energy and timing aware synchronous programming. In: International Conference on Embedded Software, EMSOFT 2016, p. 10. ACM, Pittsburgh (2016)
Yu, W., Kornerup, J., Gerstlauer, A.: MASES: mobility and slack enhanced scheduling for latency-optimized pipelined dataflow graphs. In: Proceedings of the 21st International Workshop on Software and Compilers for Embedded Systems, pp. 104–109. SCOPES 2018, ACM, NY (2018)
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Honorat, A., Bourgoin, T., Miomandre, H., Desnos, K., Menard, D., Nezan, JF. (2022). Influence of Dataflow Graph Moldable Parameters on Optimization Criteria. In: Desnos, K., Pertuz, S. (eds) Design and Architecture for Signal and Image Processing. DASIP 2022. Lecture Notes in Computer Science, vol 13425. Springer, Cham. https://doi.org/10.1007/978-3-031-12748-9_7
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