PULP: A Ultra-Low Power Parallel Accelerator for Energy-Efficient and Flexible Embedded Vision

被引:0
|
作者
Francesco Conti
Davide Rossi
Antonio Pullini
Igor Loi
Luca Benini
机构
[1] University of Bologna,Department of Electrical, Electronic and Information Engineering
[2] Integrated Systems Laboratory,undefined
[3] ETH Zurich,undefined
来源
关键词
Ultra-Low Power; Embedded vision; Convolutional Neural Network; Optical flow; Motion estimation; FD-SOI; Multi-core; OpenRISC;
D O I
暂无
中图分类号
学科分类号
摘要
Novel pervasive devices such as smart surveillance cameras and autonomous micro-UAVs could greatly benefit from the availability of a computing device supporting embedded computer vision at a very low power budget. To this end, we propose PULP (Parallel processing Ultra-Low Power platform), an architecture built on clusters of tightly-coupled OpenRISC ISA cores, with advanced techniques for fast performance and energy scalability that exploit the capabilities of the STMicroelectronics UTBB FD-SOI 28nm technology. We show that PULP performance can be scaled over a 1x-354x range, with a peak theoretical energy efficiency of 211 GOPS/W. We present performance results for several demanding kernels from the image processing and vision domain, with post-layout power modeling: a motion detection application that can run at an efficiency up to 192 GOPS/W (90 % of the theoretical peak); a ConvNet-based detector for smart surveillance that can be switched between 0.7 and 27fps operating modes, scaling energy consumption per frame between 1.2 and 12mJ on a 320 ×240 image; and FAST + Lucas-Kanade optical flow on a 128 ×128 image at the ultra-low energy budget of 14 μJ per frame at 60fps.
引用
收藏
页码:339 / 354
页数:15
相关论文
共 50 条
  • [1] PULP: A Ultra-Low Power Parallel Accelerator for Energy-Efficient and Flexible Embedded Vision
    Conti, Francesco
    Rossi, Davide
    Pullini, Antonio
    Loi, Igor
    Benini, Luca
    JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, 2016, 84 (03): : 339 - 354
  • [2] Energy-Efficient Vision on the PULP Platform for Ultra-Low Power Parallel Computing
    Conti, Francesco
    Rossi, Davide
    Pullini, Antonio
    Loi, Igor
    Benini, Luca
    PROCEEDINGS OF THE 2014 IEEE WORKSHOP ON SIGNAL PROCESSING SYSTEMS (SIPS 2014), 2014, : 274 - 279
  • [3] Power Models Supporting Energy-Efficient Co-Design on Ultra-Low Power Embedded Systems
    Vi Ngoc-Nha Tran
    Barry, Brendan
    Phuong Hoai Ha
    PROCEEDINGS OF 2016 INTERNATIONAL CONFERENCE ON EMBEDDED COMPUTER SYSTEMS: ARCHITECTURES, MODELING AND SIMULATION (SAMOS), 2016, : 39 - 46
  • [4] An Ultra-Low Power and Flexible Acoustic Modem Design to Develop Energy-Efficient Underwater Sensor Networks
    Sanchez, Antonio
    Blanc, Sara
    Yuste, Pedro
    Perles, Angel
    Jose Serrano, Juan
    SENSORS, 2012, 12 (06) : 6837 - 6856
  • [5] An ultra-low power energy-efficient microsystem for hydrogen gas sensing applications
    Pour, Naser Khosro
    Krummenacher, Francois
    Kayal, Maher
    ANALOG INTEGRATED CIRCUITS AND SIGNAL PROCESSING, 2013, 77 (02) : 155 - 168
  • [6] An ultra-low power energy-efficient microsystem for hydrogen gas sensing applications
    Naser Khosro Pour
    François Krummenacher
    Maher Kayal
    Analog Integrated Circuits and Signal Processing, 2013, 77 : 155 - 168
  • [7] Discrete Cosine Transform Hardware Accelerator in Parallel Ultra-low Power System
    Duspara, Alen
    Kovac, Mario
    Mlinaric, Hrvoje
    PROCEEDINGS OF 63RD INTERNATIONAL SYMPOSIUM ELMAR-2021, 2021, : 169 - 172
  • [8] An Energy-Efficient IoT node for HMI applications based on an ultra-low power Multicore Processor
    Kartsch, Victor
    Guermandi, Marco
    Benatti, Simone
    Montagna, Fabio
    Benini, Luca
    2019 IEEE SENSORS APPLICATIONS SYMPOSIUM (SAS), 2019,
  • [9] Energy efficient system for tactile data decoding using an ultra-low power parallel platform
    Magno, M.
    Ibrahim, A.
    Pullini, A.
    Valle, M.
    Benini, L.
    2017 FIRST NEW GENERATION OF CAS (NGCAS), 2017, : 17 - 20
  • [10] Energy-efficient switching scheme for ultra-low voltage SAR ADC
    Wu, Aidong
    Wu, Jianhui
    Huang, Jun
    ANALOG INTEGRATED CIRCUITS AND SIGNAL PROCESSING, 2017, 90 (02) : 507 - 511