@inproceedings{a969a97ed0be4418b0af9e97daf78299,
title = "Transport Triggered Array Processor for Vision Applications",
abstract = "Low-level sensory data processing in many Internet-of-Things (IoT) devices pursue energy efficiency by utilizing sleep modes or slowing the clocking to the minimum. To curb the share of stand-by power dissipation in those designs, ultra-low-leakage processes are employed in fabrication. Those limit the clocking rates significantly, reducing the computing throughputs of individual cores. In this contribution we explore compensating for the substantial computing power needs of a vision application using massive parallelism. The Processing Elements (PE) of the design are based on Transport Triggered Architecture. The fine grained programmable parallel solution allows for fast and efficient computation of learnable low-level features (e.g. local binary descriptors and convolutions). Other operations, including Max-pooling have also been implemented. The programmable design achieves excellent energy efficiency for Local Binary Patterns computations.",
keywords = "Binary Patterns, Computer vision, Embedded systems, Internet-of-Things, Massive processing arrays",
author = "Safarpour Mehdi and Hautala Ilkka and {Bordallo L{\'o}pez}, Miguel and Olli Silv{\'e}n",
year = "2019",
doi = "10.1007/978-3-030-27562-4_26",
language = "English",
isbn = "978-3-030-27561-7",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "361--372",
editor = "Maxime Pelcat and Matthias Jung and Pnevmatikatos, {Dionisios N.}",
booktitle = "Embedded Computer Systems: Architectures, Modeling, and Simulation. SAMOS 2019",
address = "Germany",
note = "19th International Conference on Embedded Computer Systems, SAmos 2019 ; Conference date: 07-07-2019 Through 11-07-2019",
}