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“CPS”
Why all the fuss?
By: Flemming CHRISTENSEN
Managing Director
Flemming.C@Sundance.com
linkedin.com/in/flemming-christensen-649987
Mobile: +44 07850 911 417
Skype: “Flemming_Sundance”
www.sundance.com
2
1. The Sundance ‘Kids’
- who are we?
2. Open Hardware Repository
- CERN’s idea – www.ohr.org
3. Why all public funded R&D should follow this idea!
- what has Sundance done already?
4. Why all the fuss about Cyber-Physical Systems?
- what goes around comes around!
5. TULIPP Project
- Just another CPS idea 
15’ish MINUTES TO COVER…..
3
Electronics
Design, Manufacturing & Test
Established in 1989 by Flemming CHRISTENSEN
• Employee Owned and a ’Life-Style’ company
• 11x people with 300+ years experince
• ISO9001:2015 accredited
• Always designed and built our own products
4
Self Adaptive Heterogeneous
ManyCore on Flexible Tiles
• FlexTiles Platform
• Dual Virtex-6 SX475 FPGAs
• Up to 40x MicroBlaze CPU per board
• EU FP7 Project – www.FlexTiles.eu
5
Embedded Multi-Core Mixed
Criticality Applications
• EMC2 Development Platform
• Intergrated Zynq w. ARM + FPGA
• Support for Xilinx SDSoC Tools
Artemis Project - http://www.artemis-emc2.eu/
6
Towards Ubiquitous Low-power
Image Processing Platforms
•Tulipp Platform
• Xilinx Zynq SoC w. ARMs + FPGA fabric
• Support for Xilinx SDSoC Tools
• Movidus MultiCore CPUs/DSPs
• NVIDIA SoC w. ARMs and GPU
• H2020 Project – www.Tulipp.eu
7
Intelligent decisions
from vineyard robots
H2020 Project – www.vinescout.eu – GA 737669
Avoid Vendor lock-in
…
8
Why Open Hardware
o Design Reuse
Enjoy what other people have
done
o Well established standards
o Ethernet, PCIe, WISHBONE
o Peer Review
Enjoy contribution from other people
o Rigorous design process
9
o Design Reuse
Why Open Hardware
Enjoy what other people have done
o Well established
o PC/104, VITA, PCIe, WISHBONE
10
Why Open Hardware
o Dissemination of knowledge
Make a
contribution
o Not Free as Free beer
Healthy relationship with companies
o Need to make a living!
o Open projects have paid developers
o Freedom
11
Open: a Win – Win Situation
oDesigns with added value
o Freedom to use, improve and produce
o Manufacturing, Testing, Warranty, Support
oBetter designs
o Review, Optimize
o More users, more feedback
oOpen products are real products
o CERN has designed over ten Open products
o Produced, sold and supported by different companies
o Products used by many institutes and industry
oFun
12
Open Hardware Repository
www.ohwr.org
o 100 active projects
o 70 initiated by CERN, 30 outside
o 60 hardware designs, 40 IP blocks
o 140 active developers
o 12 companies
o 10 research centers
www.ohwr.org
13
Open Hardware is commercial
Commercial
Non-
commercial
Open
Winning
combination.
Best of both worlds.
Whole burden falls
on developers.
Not scalable.
Proprietary Vendor lock-in.
Dedicated, non-
reusable projects.
14
 https://www.ohwr.org/projects/emc2-dp/wiki
 http://www.sundance.technology/som-cariers/pc104-boards/
Sundance First Contribution
15
 https://www.ohwr.org/projects/vs-1/wiki
 http://tulipp.eu/public-deliverables/d2-1-first-instance-of-power-efficient-platform/
Sundance Next Contribution
16
 https://www.ohwr.org/projects/xxx/wiki
 https://vinescout.eu/web/wp-content/uploads/2017/12/D1.1a_Deployment-of-prototype-I.pdf
Sundance Next Contribution
17
‘Cyber-Physical System =
“Just another keyword?”
18
To confused EU to give us money!
‘CPS’ – only 70 years old!
19
Many Partners + a few Workers 
• Thales :
Coordinator & 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
20
What is Tulipp?
Bringing energy efficiency from chip level to system level
Intensive Processing Embedded
Constraints
Time-to-market / Cost-
sensitive
Source: http://www.lnci.org.au
Goal: Safer driving experienceGoal: Bring intelligence to the drones Goal: Reduce Radiation Dose by 75%
21
Work Package Overviews
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
22
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
23
Pedestrian
detection
Safety
application
Car
integration
The Use Case
ADAS use case
24
Unmanned Aerial Vehicle 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
25
Typical Processing Platform
Component tools
Operating System
Processor
Toolchain
Reference Platform
Memory
IO
Processor
26
Pick a SoC, please
27
Focus on the Tulipp Starter-Kit
Available during the final tutorial
• Based on Xilinx Zynq UltraScale+, ZU4/EV
• Power aware RT operating system
• Toolchain support for efficient implementation
• Sample applications
• The TULIPP Handbook
28
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.
29
TULIPP Guidelines
30
Focus on the HandBook
Make it easier to build an energy efficient image processing platform
• Introduction: Low power & energy efficient image processing platforms
 Challenges & trends for the application domain & the associated platforms
• Hardware platforms
• Energy efficient GPUs
• Real-Time Operating systems
• Performance analysis Tools
• Safety critical toolchains & libraries
• Recipes, implementation examples & use cases
31
Join the Handbook Efforts
Leave a legacy!
32
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
33
Advisory Board Members
34
Next Project… - with you?
35
www.sundance.com
TULIPP DEMO
36

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Why all the fuss about CPS

  • 1. “CPS” Why all the fuss? By: Flemming CHRISTENSEN Managing Director Flemming.C@Sundance.com linkedin.com/in/flemming-christensen-649987 Mobile: +44 07850 911 417 Skype: “Flemming_Sundance” www.sundance.com
  • 2. 2 1. The Sundance ‘Kids’ - who are we? 2. Open Hardware Repository - CERN’s idea – www.ohr.org 3. Why all public funded R&D should follow this idea! - what has Sundance done already? 4. Why all the fuss about Cyber-Physical Systems? - what goes around comes around! 5. TULIPP Project - Just another CPS idea  15’ish MINUTES TO COVER…..
  • 3. 3 Electronics Design, Manufacturing & Test Established in 1989 by Flemming CHRISTENSEN • Employee Owned and a ’Life-Style’ company • 11x people with 300+ years experince • ISO9001:2015 accredited • Always designed and built our own products
  • 4. 4 Self Adaptive Heterogeneous ManyCore on Flexible Tiles • FlexTiles Platform • Dual Virtex-6 SX475 FPGAs • Up to 40x MicroBlaze CPU per board • EU FP7 Project – www.FlexTiles.eu
  • 5. 5 Embedded Multi-Core Mixed Criticality Applications • EMC2 Development Platform • Intergrated Zynq w. ARM + FPGA • Support for Xilinx SDSoC Tools Artemis Project - http://www.artemis-emc2.eu/
  • 6. 6 Towards Ubiquitous Low-power Image Processing Platforms •Tulipp Platform • Xilinx Zynq SoC w. ARMs + FPGA fabric • Support for Xilinx SDSoC Tools • Movidus MultiCore CPUs/DSPs • NVIDIA SoC w. ARMs and GPU • H2020 Project – www.Tulipp.eu
  • 7. 7 Intelligent decisions from vineyard robots H2020 Project – www.vinescout.eu – GA 737669
  • 9. Why Open Hardware o Design Reuse Enjoy what other people have done o Well established standards o Ethernet, PCIe, WISHBONE o Peer Review Enjoy contribution from other people o Rigorous design process 9
  • 10. o Design Reuse Why Open Hardware Enjoy what other people have done o Well established o PC/104, VITA, PCIe, WISHBONE 10
  • 11. Why Open Hardware o Dissemination of knowledge Make a contribution o Not Free as Free beer Healthy relationship with companies o Need to make a living! o Open projects have paid developers o Freedom 11
  • 12. Open: a Win – Win Situation oDesigns with added value o Freedom to use, improve and produce o Manufacturing, Testing, Warranty, Support oBetter designs o Review, Optimize o More users, more feedback oOpen products are real products o CERN has designed over ten Open products o Produced, sold and supported by different companies o Products used by many institutes and industry oFun 12
  • 13. Open Hardware Repository www.ohwr.org o 100 active projects o 70 initiated by CERN, 30 outside o 60 hardware designs, 40 IP blocks o 140 active developers o 12 companies o 10 research centers www.ohwr.org 13
  • 14. Open Hardware is commercial Commercial Non- commercial Open Winning combination. Best of both worlds. Whole burden falls on developers. Not scalable. Proprietary Vendor lock-in. Dedicated, non- reusable projects. 14
  • 18. ‘Cyber-Physical System = “Just another keyword?” 18 To confused EU to give us money!
  • 19. ‘CPS’ – only 70 years old! 19
  • 20. Many Partners + a few Workers  • Thales : Coordinator & 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 20
  • 21. What is Tulipp? Bringing energy efficiency from chip level to system level Intensive Processing Embedded Constraints Time-to-market / Cost- sensitive Source: http://www.lnci.org.au Goal: Safer driving experienceGoal: Bring intelligence to the drones Goal: Reduce Radiation Dose by 75% 21
  • 22. Work Package Overviews 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 22
  • 23. 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 23
  • 25. Unmanned Aerial Vehicle 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 25
  • 26. Typical Processing Platform Component tools Operating System Processor Toolchain Reference Platform Memory IO Processor 26
  • 27. Pick a SoC, please 27
  • 28. Focus on the Tulipp Starter-Kit Available during the final tutorial • Based on Xilinx Zynq UltraScale+, ZU4/EV • Power aware RT operating system • Toolchain support for efficient implementation • Sample applications • The TULIPP Handbook 28
  • 29. 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. 29
  • 31. Focus on the HandBook Make it easier to build an energy efficient image processing platform • Introduction: Low power & energy efficient image processing platforms  Challenges & trends for the application domain & the associated platforms • Hardware platforms • Energy efficient GPUs • Real-Time Operating systems • Performance analysis Tools • Safety critical toolchains & libraries • Recipes, implementation examples & use cases 31
  • 32. Join the Handbook Efforts Leave a legacy! 32
  • 33. 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 33
  • 35. Next Project… - with you? 35 www.sundance.com