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This project has received funding from
the European Union’s Horizon 20 20
research and innovation programme
under grant ag...
8 Partners
• Thales : Coordinator and Medical
use case
• Sundance : Hardware
• Hipperos : Operating system
• Synective Lab...
Outline
• Project objectives
• Main outcomes
• Advisory Board and Ecosystem
WP presentation
WP7: Management, Coordination
LABEL : Marketing, Ecosystem and Pre-normalisation
WP6: IP protection, Disse...
Starter Kit
Handbook Overview
Guidelines
Guidelines
Advice: Exploit both vectorization and multithreading for high performance on multicore
processors with vector ...
Reference Platform
Towards Ubiquitous Low-Power Image Processing Platforms
Component tools
Operating System
Processor
Tool...
• The use case is taken from the many
applications that now enter our cars, doing
emergency braking, lane keeping, etc., w...
Pedestrian
detection
Safety
application
Car
integration
The Use Case
ADAS use case
Medical imaging use case
• Real-Time X-Ray imaging for surgery
• Reduce radiation dose by 75%
• Add noise removal processi...
Medical imaging use case
TDLP
RAW IMAGE
THALES Processing
Unit
CI / ICS
UI
GigE-Vision + Msg
THALES Flat panel detector
Cu...
Unmanned Aerial Vehicle (UAV) use case
• Performs real-time stereo depth estimation to do obstacle /
collision avoidance (...
Unmanned Aerial Vehicle (UAV) use case
• Uses state-of-the art stereo algorithms (image correlation)
• Produces a distance...
TULIPP Hardware Node
• Now – Zynq SoC SoM • Soon– Zynq MPSoC SoM
40mm x 50 mm – Z7030 40mm x 50 mm - ZU5EV
TULIPP System Node
Low-Power Image Processing RTOS
Needs OS
- high reliability,
- low power,
- hard real-time
- high performance
This kind of...
STHEM: The TULIPP Tool-chain
Status:
• Xilinx SDSoC has been extended to
support the current platform
• Support for HIPPER...
TULIPP in the news
20
Advisory Board and EcoSystem
Advisory
Board
(WP6)
Reference
Platform
(WP1)
Tulipp Guide, implementation and demos
Ask for ...
Advisory Board Members
22
Advisory Board and EcoSystem
• Pledge
• Interconnectivity
• Faster time-to-market
• Open standards
Prochain SlideShare
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Tulipp_H2020_Hipeac'17 Conference_PEPGUM Workshop_January 017

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Tulipp: Towards Ubiquitous Low-power Image Processing Platforms

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Tulipp_H2020_Hipeac'17 Conference_PEPGUM Workshop_January 017

  1. 1. This project has received funding from the European Union’s Horizon 20 20 research and innovation programme under grant agreement No 688403 www.tulipp.eu TULIPP Place : Date : PEGPUM Workshop https://www.hipeac.net/events/activities/7435/pegpum/ Project Overview HiPEAC’17, Stockholm 24th of January 2017 Philippe Millet, Thales, Coordinator
  2. 2. 8 Partners • Thales : Coordinator and Medical use case • Sundance : Hardware • Hipperos : Operating system • Synective Labs : ADAS use case • Efficient Innovation : Management • Fraunhofer IOSB : UAV use case • Ruhr Universität Bochum : FPGA tools • NTNU : Performance tools
  3. 3. Outline • Project objectives • Main outcomes • Advisory Board and Ecosystem
  4. 4. WP presentation WP7: Management, Coordination LABEL : Marketing, Ecosystem and Pre-normalisation WP6: IP protection, Dissemination, Communication, Advisory Board and Exploitation preparation WP1: Reference platform definition (Interfaces & implementation Rules) Instantiations WP2: Hardware WP4: Programming Toolchain WP3: Runtime, API, Libraries & OS feedback WP5 : Usecases description and Integration and platform validation
  5. 5. Starter Kit
  6. 6. Handbook Overview
  7. 7. Guidelines
  8. 8. Guidelines Advice: Exploit both vectorization and multithreading for high performance on multicore processors with vector units such as the ARM Cortex A9. On these architectures, utilizing all hardware execution resources is key to achieve high performance [2] [4, 5]. Recommended implementation method: Use OpenMP. OpenMP is a widely supported parallel programming API that enables programmers to express vectorization and multithreading operations concisely using compiler directives. Programmers need not worry about specifying scheduling and synchronization operations in code. These are handled transparently by the OpenMP runtime system. See the official OpenMP examples[6] to understand in more detail about exploiting vectorization and multithreading simultaneously.
  9. 9. Reference Platform Towards Ubiquitous Low-Power Image Processing Platforms Component tools Operating System Processor Toolchain Reference Platform Memory IO Processor
  10. 10. • The use case is taken from the many applications that now enter our cars, doing emergency braking, lane keeping, etc., with direction towards autonomous cars • The chosen image processing algorithm for the use case is pedestrian detection that typically is used for emergency braking and driver assistance systems. • Pedestrian detection is today mostly made by either using Viola/Jones classifiers or Deep Learning • Viola Jones classifying has been chosen due to its more challenging memory access patterns ADAS use case
  11. 11. Pedestrian detection Safety application Car integration The Use Case ADAS use case
  12. 12. Medical imaging use case • Real-Time X-Ray imaging for surgery • Reduce radiation dose by 75% • Add noise removal processing with critical real-time constraints
  13. 13. Medical imaging use case TDLP RAW IMAGE THALES Processing Unit CI / ICS UI GigE-Vision + Msg THALES Flat panel detector Customer system UI GigE-Vision + Msg CI / ICS Nano Processing Unit Inside the detector Based on SoC (credit card size board) Customer system THALES Flat panel detector Before Tulipp After Tulipp
  14. 14. Unmanned Aerial Vehicle (UAV) use case • Performs real-time stereo depth estimation to do obstacle / collision avoidance (for an UAV), i.e. to detect obstacles in direction of flight • Based on dual cameras
  15. 15. Unmanned Aerial Vehicle (UAV) use case • Uses state-of-the art stereo algorithms (image correlation) • Produces a distance image, i.e. where the image data shows the distance to each object
  16. 16. TULIPP Hardware Node • Now – Zynq SoC SoM • Soon– Zynq MPSoC SoM 40mm x 50 mm – Z7030 40mm x 50 mm - ZU5EV
  17. 17. TULIPP System Node
  18. 18. Low-Power Image Processing RTOS Needs OS - high reliability, - low power, - hard real-time - high performance This kind of RTOS is not (yet) available today, as current GPOS (e.g. Linux) or RTOS lack one or more of the required features and performance. Specific Image processing Needs - supporting the hardware accelerators - the libraries needed for image processing.
  19. 19. STHEM: The TULIPP Tool-chain Status: • Xilinx SDSoC has been extended to support the current platform • Support for HIPPEROS OS is underway Insights: • Significant effort has been invested into the development of vendor tools • STHEM fills the productivity gaps between existing tools Support uTilities for Heterogeneous Embedded image processing (STHEM) •Supports development for all platform components •Map source files of the application to the appropriate tool chain •Retrieve OS configuration from the developer Development and Mapping •Boot OS with selected configuration (if needed due to changed configuration) •Update files (binaries, bitfiles, etc.) •Initialise the reconfigurable logic (if needed) •Start the application with the requested instrumentation Runner •Analyses performance results and presents findings to the developer Analyser
  20. 20. TULIPP in the news 20
  21. 21. Advisory Board and EcoSystem Advisory Board (WP6) Reference Platform (WP1) Tulipp Guide, implementation and demos Ask for review / advise Roles in the project: Provide information about standards Give feedback on the approach Early adopters Sys temEco AB: first step to the ecosystem
  22. 22. Advisory Board Members 22
  23. 23. Advisory Board and EcoSystem • Pledge • Interconnectivity • Faster time-to-market • Open standards

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