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49th Intelligent Sensing Program
Sensing in Precision (Digital) Agriculture
Sundance Multiprocessor Technology Ltd.
THE COMPANY
Established in 1989 by Flemming CHRISTENSEN
• Employee Owned and a ’Life-Style’ company
• 12x people with 300+ years experince
• 4x with accredited Xilinx FPGA training
• Always designed and built our own products
• BSI - ISO9001-2015 certified, since 2003
Techology Focus
• Acceleration & Vision,
• Sensor & Robotics
2
• Overview
• Hardware features
• Sensors compatibility
• Industry compatibility
• Open software and firmware
• PYNQ (Python) support
• EDGE AI support
• Applications
• Endorsement
• Summary
• What Next?
3
OVERVIEW OF THE VCS-1 SYSTEM
A Xilinx Zynq MPSoC is the ‘heart’ of VCS-1 and provide 64-bit processor
scalability while combining real-time control with soft and hard engines for
graphics, video, waveform, and FPGA acceleration, using a Trenz TE0820
“SoM”.
HARDWARE FEATURES
4
Multiprocessor system
ZU4EV
TEO820-ZU4EV
HARDWARE FEATURES
Connectivity:
 FM191-R; FMC-LPC to:
 15x Digital I/Os [DB9]
 12x Analogue Inputs [DB9]
 8x Analogue Outputs [DB9]
 1x Expansion [SEIC]
 FM191-U; SEIC to:
 4x USB3.0 [USB-c]
 28x GPIO [40-pin GPIO]
 FM191-A1; 40-pin GPIO
 28x GPIO [DB9]
5FM191
I/O interfaces
A custom enclosure was specially designed
for accommodating the VCS-1 system, called
PC104-Blade
6
HARDWARE FEATURES
Rugged Enclosure
The VCS-1 is compatible with a wide range of sensors, like:
Depth sensor. Interface USB3.0
Intel RealSense - D435
SENSORS COMPATIBILITY
7
Tracking sensor. Interface USB3.0
Intel RealSense – T265
INDUSTRY COMPATIBILITY
VCS-1 features:
 Raspberry Pi version 3 model
B and Arduino compatible
 Compatible with most of the
Arduino/Raspberry Pi sensors
and actuators
 USB3.0 & Ethernet ports for
interfacing with a wide range
of sensors
8
HARDWARE DEBUG TOOLS
9
VCS hardware debugging is easy with industry
standard JTAG directedly into the Zynq MPSoC
 TULIPP’s LynSyn Power Monitor & Toolchain
 http://bit.ly/VCS_Lynsyn
 http://bit.ly/VCS_Tulipp_Toolchain
 Xilinx JTAG Platform Hardware Cable
 http://bit.ly/VCS_JTAG_Cable
 Xilinx JTAG SmartLynq Cable
 http://bit.ly/VCS_SmartLynq_Cable
OPEN SOURCE
Open Source and online documentation:
 CERN’s Open Hardware Repository
 http://bit.ly/VCS_OHR
 VCS Hardware
 http://bit.ly/VCS_Hardware
 VCS Software
 http://bit.ly/VCS_Software
 VCS Firmware
 http://bit.ly/VCS_FM191_firmware
10
VCS-1 DEVELOPMENT TOOLS
VCS’s “Processing System” (PS) running within the
ARM A53 CPUs, is supported by Linux:
► http://bit.ly/VCS_Xilinx_Linux
► https://ubuntu.com/
VCS has a version of Ubuntu 16.04 LTS and 18.04 LTS
ported and for free download.
Xilinx also offers free option of an embedded Linux
for Zynq, called PetaLinux:
► http://bit.ly/VCS_Peta_Linux
The VCS’s “Programable Logic” (PL) – that is the
‘classic’ FPGA fabric - is supported by the free
WebPACK & SD-SoC environment from Xilinx:
► http://bit.ly/VCS_Vivado_Zynq
► http://bit.ly/VCS_C_to_VHDL_SDSoC
11
PROGRAMMING TOOLS
 MQTT compatible
 OASIS standard
 Machine-to-machine (M2M)/"Internet of
Things" connectivity protocol.
 OpenCV compatible
 Open source computer vision and machine
learning software library.
 ROS compatible
 The Robot Operating System (ROS) is a set of
software libraries and tools that helps
building robot applications.
 ROS2 ready
 PYNQ compatible
 PYNQ is an open-source project from
Xilinx that is utilizing Python & Jupyter to
make it easy to design embedded systems
with Zynq 12
 The Xilinx Edge-AI Platform provides
comprehensive tools and models which
utilize unique deep compression and
hardware-accelerated Deep Learning
technology.
 The platform provides efficient,
convenient and economical inference
deployments for embedded-CPU-based
FPGAs.
 The Xilinx AI team consists of renowned
researchers and experienced
professionals known for their pioneering
work in the field of deep learning.
13
EDGE-AI
Xilinx Edge - AI
The VCS-1 is fully compatible with the Xilinx Edge-AI.
Key Features
Provides a complete set of toolchains with compression, compilation, deployment and profiling.
Supports mainstream frameworks and the latest models capable of diverse deep learning tasks
Provides a lightweight standard C/C++ programming API (no RTL programming knowledge required)
Scalable board support from cost-optimized to performance-driven platforms
Supports system integration with both SDSoC and Vivado
DNNDK consists of:
DEep ComprEssioN Tool (DECENT)
Deep Neural Network Compiler (DNNC)
Neural Network Runtime (N2Cube)
Profiler
14
EDGE-AI
Xilinx-DPU
DNNDK™
(Deep Neural Network Development Kit)
15
EDGE-AI
Xilinx
Edge-AI
Frameworks
Xilinx Edge-AI Platform supports a number of industry-standard frameworks
• TensorFlow is an open-source framework developed by Google.
• CAFFE is an open-source framework developed at UC Berkley.
• Darknet is an open-source framework developed by Joseph Redmon.
• Keras is a high-level neural networks API, written in Python and capable of running
on top of TensorFlow.
16
EDGE-AI
Models
17
APPLICATIONS
HTTP://BIT.LY/VCS1_SLAM
http://bit.ly/VCS_Edge-AI
18
HTTP://BIT.LY/VCS1_NDVI
HTTP://BIT.LY/VCS1_NN
VCS-1 APPLICATIONS
19
VCS-1 APPLICATIONS
HTTP://BIT.LY/VCS1_VINESCOUT
20
HTTP://BIT.LY/VINESCOUT_VCS_SUMMIT_XL
HTTP://BIT.LY/TULLIP_USE_CASE_UAV
VCS-1 APPLICATIONS
VCS-1 ENDORSEMENT
21
VCS-1 ENDORSEMENT
22
http://semfire.ingeniarius.pt/
SUMMARY
The VCS-1 has the following characteristics:
1. High performance, using ‘state-of-the-art’ Xilinx
Zynq MPSoC
2. Low power consumption (typical 10W)
3. Highly compatible with a wide range of
commercially available sensors and actuators
4. Highly optimised for computer vision applications,
embedded AI and Deep Learning
5. Fully reconfigurable and expandable
using PC/104 form-factor (90mm x 96mm)
6. Compatible with the most common Linux distros
(I.e. Ubuntu, Debian, RedHat, CentOS, etc.)
7. Software support for ROS and MQTT
8. Python and C/C++ support
23
WHAT’S NEXT ?
 Research topics:
 Object detection, changes detection, visual-servoing
 Autonomous navigation, object grasping
 2D>3D Pose estimation, perception, AI in robotics
 Sundance University Program (SUP)
 Access to hardware prototypes
 Advisory Board Members
 BSC/MSc/PhD Internships
 R&D Project proposals
 H2020, Innovate-UK, EuroSTARS
 EPSRC/BBSRC/UKRI/SPRINT
 https://www.smartagrihubs.eu/portal/network
Want to know more about Sundance in R&D Projects ?
https://www.sundance.com/sundance-in-eu-projects-programs/
24
WHAT’S NEXT ?
25
WHAT’S NEXT ?
26
27
Sundance Multiprocessor Technology, Ltd.
Pedro Machado Pedro.M@sundance.com
Flemming Christensen Flemming.C@sundance.com
www.SUNDANCE.com

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Sundance at the 49th Intelligent Sensing Program

  • 1. 49th Intelligent Sensing Program Sensing in Precision (Digital) Agriculture Sundance Multiprocessor Technology Ltd.
  • 2. THE COMPANY Established in 1989 by Flemming CHRISTENSEN • Employee Owned and a ’Life-Style’ company • 12x people with 300+ years experince • 4x with accredited Xilinx FPGA training • Always designed and built our own products • BSI - ISO9001-2015 certified, since 2003 Techology Focus • Acceleration & Vision, • Sensor & Robotics 2
  • 3. • Overview • Hardware features • Sensors compatibility • Industry compatibility • Open software and firmware • PYNQ (Python) support • EDGE AI support • Applications • Endorsement • Summary • What Next? 3 OVERVIEW OF THE VCS-1 SYSTEM
  • 4. A Xilinx Zynq MPSoC is the ‘heart’ of VCS-1 and provide 64-bit processor scalability while combining real-time control with soft and hard engines for graphics, video, waveform, and FPGA acceleration, using a Trenz TE0820 “SoM”. HARDWARE FEATURES 4 Multiprocessor system ZU4EV TEO820-ZU4EV
  • 5. HARDWARE FEATURES Connectivity:  FM191-R; FMC-LPC to:  15x Digital I/Os [DB9]  12x Analogue Inputs [DB9]  8x Analogue Outputs [DB9]  1x Expansion [SEIC]  FM191-U; SEIC to:  4x USB3.0 [USB-c]  28x GPIO [40-pin GPIO]  FM191-A1; 40-pin GPIO  28x GPIO [DB9] 5FM191 I/O interfaces
  • 6. A custom enclosure was specially designed for accommodating the VCS-1 system, called PC104-Blade 6 HARDWARE FEATURES Rugged Enclosure
  • 7. The VCS-1 is compatible with a wide range of sensors, like: Depth sensor. Interface USB3.0 Intel RealSense - D435 SENSORS COMPATIBILITY 7 Tracking sensor. Interface USB3.0 Intel RealSense – T265
  • 8. INDUSTRY COMPATIBILITY VCS-1 features:  Raspberry Pi version 3 model B and Arduino compatible  Compatible with most of the Arduino/Raspberry Pi sensors and actuators  USB3.0 & Ethernet ports for interfacing with a wide range of sensors 8
  • 9. HARDWARE DEBUG TOOLS 9 VCS hardware debugging is easy with industry standard JTAG directedly into the Zynq MPSoC  TULIPP’s LynSyn Power Monitor & Toolchain  http://bit.ly/VCS_Lynsyn  http://bit.ly/VCS_Tulipp_Toolchain  Xilinx JTAG Platform Hardware Cable  http://bit.ly/VCS_JTAG_Cable  Xilinx JTAG SmartLynq Cable  http://bit.ly/VCS_SmartLynq_Cable
  • 10. OPEN SOURCE Open Source and online documentation:  CERN’s Open Hardware Repository  http://bit.ly/VCS_OHR  VCS Hardware  http://bit.ly/VCS_Hardware  VCS Software  http://bit.ly/VCS_Software  VCS Firmware  http://bit.ly/VCS_FM191_firmware 10
  • 11. VCS-1 DEVELOPMENT TOOLS VCS’s “Processing System” (PS) running within the ARM A53 CPUs, is supported by Linux: ► http://bit.ly/VCS_Xilinx_Linux ► https://ubuntu.com/ VCS has a version of Ubuntu 16.04 LTS and 18.04 LTS ported and for free download. Xilinx also offers free option of an embedded Linux for Zynq, called PetaLinux: ► http://bit.ly/VCS_Peta_Linux The VCS’s “Programable Logic” (PL) – that is the ‘classic’ FPGA fabric - is supported by the free WebPACK & SD-SoC environment from Xilinx: ► http://bit.ly/VCS_Vivado_Zynq ► http://bit.ly/VCS_C_to_VHDL_SDSoC 11
  • 12. PROGRAMMING TOOLS  MQTT compatible  OASIS standard  Machine-to-machine (M2M)/"Internet of Things" connectivity protocol.  OpenCV compatible  Open source computer vision and machine learning software library.  ROS compatible  The Robot Operating System (ROS) is a set of software libraries and tools that helps building robot applications.  ROS2 ready  PYNQ compatible  PYNQ is an open-source project from Xilinx that is utilizing Python & Jupyter to make it easy to design embedded systems with Zynq 12
  • 13.  The Xilinx Edge-AI Platform provides comprehensive tools and models which utilize unique deep compression and hardware-accelerated Deep Learning technology.  The platform provides efficient, convenient and economical inference deployments for embedded-CPU-based FPGAs.  The Xilinx AI team consists of renowned researchers and experienced professionals known for their pioneering work in the field of deep learning. 13 EDGE-AI Xilinx Edge - AI The VCS-1 is fully compatible with the Xilinx Edge-AI.
  • 14. Key Features Provides a complete set of toolchains with compression, compilation, deployment and profiling. Supports mainstream frameworks and the latest models capable of diverse deep learning tasks Provides a lightweight standard C/C++ programming API (no RTL programming knowledge required) Scalable board support from cost-optimized to performance-driven platforms Supports system integration with both SDSoC and Vivado DNNDK consists of: DEep ComprEssioN Tool (DECENT) Deep Neural Network Compiler (DNNC) Neural Network Runtime (N2Cube) Profiler 14 EDGE-AI Xilinx-DPU DNNDK™ (Deep Neural Network Development Kit)
  • 15. 15 EDGE-AI Xilinx Edge-AI Frameworks Xilinx Edge-AI Platform supports a number of industry-standard frameworks • TensorFlow is an open-source framework developed by Google. • CAFFE is an open-source framework developed at UC Berkley. • Darknet is an open-source framework developed by Joseph Redmon. • Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow.
  • 23. SUMMARY The VCS-1 has the following characteristics: 1. High performance, using ‘state-of-the-art’ Xilinx Zynq MPSoC 2. Low power consumption (typical 10W) 3. Highly compatible with a wide range of commercially available sensors and actuators 4. Highly optimised for computer vision applications, embedded AI and Deep Learning 5. Fully reconfigurable and expandable using PC/104 form-factor (90mm x 96mm) 6. Compatible with the most common Linux distros (I.e. Ubuntu, Debian, RedHat, CentOS, etc.) 7. Software support for ROS and MQTT 8. Python and C/C++ support 23
  • 24. WHAT’S NEXT ?  Research topics:  Object detection, changes detection, visual-servoing  Autonomous navigation, object grasping  2D>3D Pose estimation, perception, AI in robotics  Sundance University Program (SUP)  Access to hardware prototypes  Advisory Board Members  BSC/MSc/PhD Internships  R&D Project proposals  H2020, Innovate-UK, EuroSTARS  EPSRC/BBSRC/UKRI/SPRINT  https://www.smartagrihubs.eu/portal/network Want to know more about Sundance in R&D Projects ? https://www.sundance.com/sundance-in-eu-projects-programs/ 24
  • 27. 27 Sundance Multiprocessor Technology, Ltd. Pedro Machado Pedro.M@sundance.com Flemming Christensen Flemming.C@sundance.com www.SUNDANCE.com