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www.tulipp.eu
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688403
H2020
TULIPP - Towards Ubiquitous Low-
power Image Processing Platforms
Overall Project Presentation
Tobias Kalb
Ruhr-University Bochum
contact@tulipp.eu
2 | 13
TheinformationcontainedinthisdocumentandanyattachmentsarethepropertyofTulippconsortium.Youareherebynotifiedthatanyreview,dissemination,
distribution,copyingorotherwiseuseofthisdocumentmustbedoneinaccordancewiththeCAoftheproject(TRT/DJ/ACU).Templateversion1.0
H2020
Introduction
Overview
• TULIPP: Towards Ubiquitous Low-power Image Processing Platforms
• Horizon 2020: EU Framework Programme for Research and Innovation,
Grant Agreement 688403
• Duration: February 2016 – January 2019 (36 Months)
• Consortium: 8 Partners
• Thales S.A., France (Coordinator)
• Ruhr-University Bochum (RUB), Germany
• Sundance Multiprocessor Technology Ltd., UK
• HIPPEROS S.A., Belgium
• Fraunhofer IOSB, Germany
• Norwegian University of Science and Technology (NTNU), Norway
• Synective Labs AB, Sweden
• Efficient Innovation, France
• Webpage: www.tulipp.eu
3 | 13
TheinformationcontainedinthisdocumentandanyattachmentsarethepropertyofTulippconsortium.Youareherebynotifiedthatanyreview,dissemination,
distribution,copyingorotherwiseuseofthisdocumentmustbedoneinaccordancewiththeCAoftheproject(TRT/DJ/ACU).Templateversion1.0
H2020
Introduction
Problem
A lot of modern industrial systems rely on embedded vision-based applications
• Increasing number of sensors, amount of data, data bandwidth etc.
• Demand for high-performance, low-power and heterogeneous computing
• Build into small embedded devices where size, weight and power matter
• Embedded systems for image processing are highly specialized systems
https://commons.wikimedia.org/wiki/File:IBM_Blue_Gene_P_supercomputer.jpg
http://edablog.com/2013/08/08/blackfin-bf609-pvp/
4 | 13
TheinformationcontainedinthisdocumentandanyattachmentsarethepropertyofTulippconsortium.Youareherebynotifiedthatanyreview,dissemination,
distribution,copyingorotherwiseuseofthisdocumentmustbedoneinaccordancewiththeCAoftheproject(TRT/DJ/ACU).Templateversion1.0
H2020
Introduction
General Goals of TULIPP
TULIPP aims to push forward a reference
platform for embedded image processing
applications in order to
• Define implementation rules for
vision-based applications
• Provide guidelines for guaranteed
high performance and low power
• Reduce development time and costs
With the focus on embedded vision-based applications TULIPP will
• Set up an ecosystem
• Work closely with standardization organizations
• Propose new standards derived from the reference platform
5 | 13
TheinformationcontainedinthisdocumentandanyattachmentsarethepropertyofTulippconsortium.Youareherebynotifiedthatanyreview,dissemination,
distribution,copyingorotherwiseuseofthisdocumentmustbedoneinaccordancewiththeCAoftheproject(TRT/DJ/ACU).Templateversion1.0
H2020
TULIPP Reference Platform
Concepts of the TULIPP Reference Platform
The goal is not to develop a fixed, generic embedded computing platform.
Instead, the TULIPP project aims to define
• Implementation rules and
• Interfaces
This allows for a flexible platform for vision-based applications featuring
• Hardware architecture:
a scalable low-power board
• Low-power, real-time
operating system and
image processing libraries
• Productivity-enhancing
toolchain
6 | 13
TheinformationcontainedinthisdocumentandanyattachmentsarethepropertyofTulippconsortium.Youareherebynotifiedthatanyreview,dissemination,
distribution,copyingorotherwiseuseofthisdocumentmustbedoneinaccordancewiththeCAoftheproject(TRT/DJ/ACU).Templateversion1.0
H2020
Hardware Architecture
Hardware Architecture
• Heterogeneous Systems-on-Chip (SoCs)
• Combinations of CPU, GPU and FPGA
• Dedicated HW accelerators
• Also dedicated real-times cores
• Appropriate hardware system
• Selection of processing elements
• Interconnections of on-chip components
• Interconnections of several SoCs
• Support advanced features
• Switch-off mechanisms
• Dynamic Voltage and
Frequency Scaling (DVFS)
• Dynamic Partial Reconfiguration (DPR)
7 | 13
TheinformationcontainedinthisdocumentandanyattachmentsarethepropertyofTulippconsortium.Youareherebynotifiedthatanyreview,dissemination,
distribution,copyingorotherwiseuseofthisdocumentmustbedoneinaccordancewiththeCAoftheproject(TRT/DJ/ACU).Templateversion1.0
H2020
Real-Time Operating System
Operating System and Low-Level Libraries
• Real-time operating system with APIs to
• Support low power
• Support image processing applications
• Run on instantiated processors
• Support heterogeneous multi-core systems
• Handle hardware resources (FPGAs)
• Implementation of communication and synchronization
• Provide for the developer
• Real-time guarantees
• Reliability
• Easy programmability
8 | 13
TheinformationcontainedinthisdocumentandanyattachmentsarethepropertyofTulippconsortium.Youareherebynotifiedthatanyreview,dissemination,
distribution,copyingorotherwiseuseofthisdocumentmustbedoneinaccordancewiththeCAoftheproject(TRT/DJ/ACU).Templateversion1.0
H2020
Toolchain
Toolchain
• A TULIPP compliant platform may have different components from
different vendors
• Expertise required for every vendor specific tool
• Lack of expertise may prevent usage of fitting hardware components
• TULIPP toolchain is a set of Eclipse-based utilities to support the developer
• STHEM - Supporting uTilities for Heterogeneous EMbedded
image processing
• Wraps around, extends and connects existing vendor tools
• Programmers use expert-written mechanisms for mapping and
optimizing applications
9 | 13
TheinformationcontainedinthisdocumentandanyattachmentsarethepropertyofTulippconsortium.Youareherebynotifiedthatanyreview,dissemination,
distribution,copyingorotherwiseuseofthisdocumentmustbedoneinaccordancewiththeCAoftheproject(TRT/DJ/ACU).Templateversion1.0
H2020
Use Cases
Use Cases
• Instantiation of reference platform is use case driven
• Verification of reference platform with image processing applications
• Medical imaging
• Automotive imaging (ADAS)
• Robotic imaging (UAV)
• Different fields of embedded applications, but similar constraints
• Performance
• Power consumption
• Size, volume and cost
• Also often real-time constraints
10 | 13
TheinformationcontainedinthisdocumentandanyattachmentsarethepropertyofTulippconsortium.Youareherebynotifiedthatanyreview,dissemination,
distribution,copyingorotherwiseuseofthisdocumentmustbedoneinaccordancewiththeCAoftheproject(TRT/DJ/ACU).Templateversion1.0
H2020
https://commons.wikimedia.org/wiki/File:113abcd_Medical_Imaging_Techniques.jpg
Medical Imaging
Medical Imaging
• Demand for high performance yet small devices
• Requires processing of large
amount of data
• Mobile imaging equipment replacing
high-end infrastructure devices
• Demand for real-time imaging
• Fast processing of image data
during surgery
• On mobile device
• TULIPP X-Ray use case aims to provide
• Reduction of radiation dose of sensors
• More powerful image processing
• Low power since heat and other
RF emission could disturb sensors
11 | 13
TheinformationcontainedinthisdocumentandanyattachmentsarethepropertyofTulippconsortium.Youareherebynotifiedthatanyreview,dissemination,
distribution,copyingorotherwiseuseofthisdocumentmustbedoneinaccordancewiththeCAoftheproject(TRT/DJ/ACU).Templateversion1.0
H2020
Automotive Imaging
Automotive Driver Assistance System (ADAS)
• Intelligent cars need more and efficient embedded devices
Image processing required for
• Driving safety
• Pedestrian safety
• More active safety systems
• Vehicle, pedestrian and object detection
• Traffic sign and lane recognition
• Night vision and surround view
• Driver monitoring
• TULIPP ADAS use case aims to provide
• Real-time, low latency high-performance
image processing
• Reliability and robustness
https://www.asdreports.com/news-10595/key-players-advanced-driver
-assistance-systems-adas-market-north-america-20152019
http://www.rcs.ei.tum.de/forschung/driver-assistance/
12 | 13
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distribution,copyingorotherwiseuseofthisdocumentmustbedoneinaccordancewiththeCAoftheproject(TRT/DJ/ACU).Templateversion1.0
H2020
Autonomous Unmanned Aerial Vehicles (UAVs)
• UAVs more common for different applications
• Surveillance, search and rescue,
logistics and research
• On-board real-time processing is
key technology
• Efficient and reliable automatic
collision avoidance needed
• Opposing constraints
• The TULIPP UAV use case aims to provide
• Optimized performance-to-weight and
power-consumption-to-weight figures
• On-board stereo vision & depth estimation
• Real-time and automatic detection of
obstacles for collision avoidance https://irevolutions.org/2014/03/24/launching-a-search
-and-rescue-challenge-for-drone-uav-pilots/
Autonomous UAV Imaging
13 | 13
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distribution,copyingorotherwiseuseofthisdocumentmustbedoneinaccordancewiththeCAoftheproject(TRT/DJ/ACU).Templateversion1.0
H2020
Advisory Board
Everyone is welcome to join and participate actively!
• Influence the technical directions in the project for your own exploitations
• Use the TULIPP eco-system and partners to network with potential suppliers and customers
• Free attendance to any TULIPP events, like workshops, tutorials and meetings
• A free TULIPP ‘SoA’ development kit at the end of the project that will be provided after participating in
the final workshop. This will include a hardware board with the operating system and a development
toolchain together with a sample image processing application
• Access to TULIPP Partners for help in using the TULIPP platform for your own products/developments
• You get listed, with short profile and logo, on the TULIPP web-site – www.TULIPP.eu/abm
Information : http://tulipp.eu/advisory-board-letter-information
Forum: http://support.tulipp.eu
E-Mail: coordinator@tulipp.eu
Web: www.tulipp.eu
Thank You!
Questions?

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