• Groene Loper 19, Flux 4.132

    5612 AP Eindhoven

    Netherlands

  • P.O. Box 513, Department of Electrical Engineering

    5612 MB Eindhoven

    Netherlands

Organization profile

Introduction / mission

The Efficient Stream Processing lab focusses on addressing the key challenges in this design flow, i.e. developing adaptive programming languages for streaming applications, platform-aware compilers, and memory-centric architectures.

Organisational profile

Efficient stream processing at the edge is critical for realizing a sustainable society. For example, intelligent camera systems monitor real time traffic with the objective to guide traffic flows thereby reducing traffic jams and pollution. Other systems in for example smart homes (building automation), health (vital signs monitoring), industry (predictive maintenance, quality control), agriculture (weather forecasting), leisure (crowd management) produce, often with regular intervals, large streams of data that need to be processed in real time. Sometimes processing in the cloud is feasible, but more often stringent timing and privacy constraints require processing of the data inside the edge devices. To deliver the required capabilities and the economic promise, research in novel design methods and architectures for efficient stream processing is critical. 

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    Projects

    Research Output

    • 22 Conference contribution
    • 12 Article
    • 2 Chapter
    • 1 Foreword/postscript

    Multi-Camera Infrared Thermography for Infant Respiration Monitoring

    Lorato, I., Stuijk, S., Meftah, M., Kommers, D., Andriessen, P., van Pul, C. & de Haan, G., 1 Sep 2020, In : Biomedical Optics Express. 11, 9, p. 4848-4861

    Research output: Contribution to journalArticleAcademicpeer-review

    Open Access
  • TDO-CIM: Transparent Detection and Offloading for Computation In-memory

    Vadivel, K., Chelini, L., BanaGozar, A., Singh, G., Corda, S., Jordans, R. & Corporaal, H., 30 Jun 2020, 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE). Di Natale, G., Bolchini, C. & Vatajelu, E-I. (eds.). Institute of Electrical and Electronics Engineers, p. 1602-1605 4 p. 9116464

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    Open Access
    File
  • 3 Downloads (Pure)

    Automatic memory-efficient scheduling of CNNs

    Waeijen, L., Sioutas, S., He, Y., Peemen, M. & Corporaal, H., 1 Jan 2019, Embedded Computer Systems: Architectures, Modeling, and Simulation - 19th International Conference, SAMOS 2019, Proceedings. Pelcat, M., Jung, M. & Pnevmatikatos, D. N. (eds.). Cham: Springer, p. 387-400 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11733 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

  • 10 Downloads (Pure)