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Products > Single Board Computers > FZ3 Card (Xilinx ZU3EG) > FZ3 Card - Deep Learning Accelerator Card |
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FZ3 Card - Deep Learning Accelerator Card |
- Xilinx Zynq UltraScale+ ZU3EG MPSoC based on 1.2 GHz Quad Arm Cortex-A53 and 600MHz Dual Cortex-R5 Cores
- 4GB DDR4 SDRAM (64-bit, 2400MHz)
- 8GB eMMC Flash, 32MB QSPI Flash, 32KB EEPROM
- USB2.0, USB3.0, Gigabit Ethernet, TF, DP, PCIe, MIPI-CSI, BT1120, USB-UART, JTAG…
- Computing Power up to 1.2TOPS, MobileNet up to 100FPS
- Ready-to-Run PetaLinux 2020.1
- Supports Xilinx Vitis Software Development Platform
- Supports Baidu's PaddlePaddle Deep Learning AI Framework
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MYIR is a Xilinx Alliance Member, welcome to use MYIR's Xilinx products!
We also offer ODM & OEM services, welcome your inquiry!
http://www.myirtech.com/xilinxseries.asp
The FZ3 Card is a powerful deep learning accelerator card based on Xilinx Zynq
UltraScale+ ZU3EG MPSoC which features a
1.2 GHz quad-core ARM Cortex-A53 64-bit application
processor, a 600MHz dual-core real-time ARM Cortex-R5 processor, a Mali400 embedded GPU and rich FPGA fabric. Besides, it
integrates 4GB DDR4, 8GB
eMMC, 32MB QSPI Flash and 32KB EEPROM as well
as many peripherals including USB 2.0, USB
3.0, Gigabit Ethernet, TF, DisplayPort (DP), PCIe interface, MIPI-CSI, BT1120
camera, USB-UART, JTAG, IO expansion interfaces, etc. The rich resources enable users to integrate intelligent hardware
easily.
FZ3 Card Top-view
FZ3 Card Bottom-view
The FZ3 Card is able to run PetaLinux 2020.1 and and provided complete BSP. It can support Xilinx Vitis Software development platform. It can also supports PaddlePaddle deep learning AI framework which is fully compatible to use Baidu Brain’s AI development tools like EasyDL, AI Studio and EasyEdge to enable developers and engineers to quickly leverage Baidu-proven technology or deploy self-defined models, enabling faster deployment. Typical applications are AI camera, AI computing device, robotics, intelligent car, intelligent electronic scale, patrol UAV and other embedded intelligent applications.
Baidu Brain’s AI development tools
Software Architecture of FZ3 Card
MYIR provides FZ3 Kit which contains the FZ3 Card with installed radiator and some necessary accessories including one power adaptor, one 16GB TF card, one mini USB cable and one mini DP to HDMI cable. It helps users start their development rapidly when getting the kit out-of-box right away.
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Features
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Description
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Dimensions
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100mm x 70mm
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PCB Layer
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12-layer
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Power Supply
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DC12V/2A
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Static Power
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About 5W
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Working Temp.
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-40°C~85°C
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Target Applications
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AI Camera, AI Computing Box, AI Robot, Smart Car, Intelligent Electronic Scale, Patrol UAV, etc.
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CPU
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Xilinx Zynq UltraScale+ XCZU3EG-1SFVC784E (ZU3EG, 784 Pin Package) MPSoC
- 1.2GHz 64 bit Quad-core ARM® Cortex™-A53
- 600MHz Dual-core ARM® Cortex™-R5 processor
- ARM Mali™-400MP2 Graphics Processor
- 16nm FinFET+ FPGA fabric
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RAM
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4GB DDR4 (64-bit)
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Flash
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8GB eMMC, 32MB QSPI, 32KB EEPROM
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Ethernet
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1 x Gigabit Ethernet
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USB
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1 x USB 2.0 Host, 1 x USB 3.0 Host
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TF Card
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1 x Micro SD Card Slot
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DP
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1 x Mini DisplayPort (4K/30fps, 2-lane)
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PCIe
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1 x PCIe 2.1 Interface (1-lane)
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MIPI-CSI
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1 x MIPI-CSI Interface (25-pin 0.3mm pitch FPC connector)
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BT1120
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1 x BT1120 Camera Interface (32-pin 0.5mm pitch FPC connector)
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Debug
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1 x Mini USB-to-UART Port
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JTAG
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1 x 6-pin 2.54mm pitch pin header
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LED
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1 x Power LED, 4 x Status LEDs (2 x Red, 2 x Green)
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Buttons
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1 x FPGA Reset Button, 1 x System Reset Button
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Others
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1 x RTC Battery Socket (AG2 or LR41 battery is recommended)
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Expansion IOs
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Two 2.54mm pitch 2 x 20-pin IO Expansion Interfaces
(1 x CAN, 1 x RS485, 2 x USB Host 2.0, 12 pairs x HD_IO, 8 pairs x HP_IO, 4 x PS_MIO)
Note: the peripheral signals brought out to the expansion interfaces are listed in maximum number. Some signals are reused. Please refer to the board schematic and processor datasheet.
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Software
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Ready to run PetaLinux 2020.1
Supports Xilinx Vitis Software Development Platform
supports PaddlePaddle deep learning AI framework
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Features of FZ3 Card
FZ3 Card in the Video
Other MYIR's Xilinx Products
http://www.myirtech.com/xilinxseries.asp
Z-turn Lite Single Board Computer (based on Zynq-7007S / Zynq-7010)
Z-turn Board V2 Single Board Computer (based on Zynq-7010 / Zynq-7020)
MYD-C7Z015 Development Board (MYC-C7Z015 CPU Module as core board, Zynq-7015)
MYD-Y7Z010/20-V2 Development Board (MYC-Y7Z010/20-V2 CPU Module as core board, Zynq-7010 / 7020)
MYD-C7Z010/20-V2 Development Board (MYC-C7Z010/20-V2 CPU Module as core board, Zynq-7010 / 7020)
MYD-CZU3EG/4EV/5EV-V2 Development Board (MYC-CZU3EG/4EG/5EV-V2 CPU Module as core board, ZU3EG/4EV/5EV)
FZ5 Card (AI Accelerator Card based on Zynq UltraScale+ ZU5EV MPSoC)
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Hardware Features
Zynq® UltraScale+™ MPSoC devices provide 64-bit processor scalability while combining real-time control with soft and hard engines for graphics, video, waveform, and packet processing. Built on a common real-time processor and programmable logic equipped platform, three distinct variants include dual application processor (CG) devices, quad application processor and GPU (EG) devices, and video codec (EV) devices.
Zynq UltraScale+ MPSoCs
The Zynq UltraScale+ family provides footprint compatibility to enable users to migrate designs from one device to another. Any two packages with the same footprint identifier code (last letter and number sequence) are footprint compatible. MYIR is using the XCZU3EG-1SFVC784E MPSoC for MYD-CZU3EG Development Board by default, the C784 package covers the widest footprint compatibilities that enable users to select devices among CG, EG and EV.
Zynq UltraScale+ MPSoC Device Migration Table
MYIR may also supply the MYC-CZU3EG CPU Modules with XCZU2CG, XCZU3CG, XCZU4EV or XCZU5EV MPSoC as options. The main features for the MPSoC devices are summarized as below.
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Device
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XCZU2CG
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XCZU3CG
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XCZU3EG
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XCZU4EV
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XCZU5EV
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Logic cells (k)
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103
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154
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154
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192
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256
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CLB Flip-Flops (K)
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94
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141
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141
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176
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234
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CLB LUTs (K)
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47
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71
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71
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88
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117
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Block RAM (Mb)
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5.3
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7.6
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7.6
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4.5
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5.1
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UltraRAM (Mb)
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-
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-
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-
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13.5
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18.0
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DSP Slices
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240
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360
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360
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728
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1,248
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GTX transceivers
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PS-GTR4x (6Gb/s)
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PS-GTR4x (6Gb/s)
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PS-GTR4x (6Gb/s)
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PS-GTR4x (6Gb/s), GTH4x (16.3Gb/s)
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PS-GTR4x (6Gb/s), GTH4x (16.3Gb/s)
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Processor Units
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Application Processor Unit
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Dual-core ARM® Cortex™-A53 MPCore™ up to 1.3GHz
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Quad-core ARM® Cortex™-A53 MPCore™ up to 1.5GHz
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Memory w/ECC
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L1 Cache 32KB I / D per core, L2 Cache 1MB, on-chip Memory 256KB
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Real-Time Processor Unit
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Dual-core ARM Cortex-R5 MPCore™ up to 600MHz
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Memory w/ECC
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L1 Cache 32KB I / D per core, Tightly Coupled Memory 128KB per core
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Graphics Processing Unit
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-
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Mali™-400 MP2 up to 667MHz
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Video Codec
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-
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H.264 / H.265
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Memory L2 Cache
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64KB
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External Memory, Connectivity, Integrated Block Functionality
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Dynamic Memory Interface
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x32/x64: DDR4, LPDDR4, DDR3, DDR3L, LPDDR3 with ECC
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Static Memory Interfaces
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NAND, 2x Quad-SPI
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High-Speed Connectivity
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PCIe® Gen2 x4, 2x USB3.0, SATA 3.1, DisplayPort, 4x Tri-mode Gigabit Ethernet
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General Connectivity
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2 x USB 2.0, 2 x SD/SDIO, 2 x UART, 2 x CAN 2.0B, 2 x I2C, 2 x SPI, 4 x 32b GPIO
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Power Management
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Full / Low / PL / Battery Power Domains
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Security
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RSA, AES, and SHA
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AMS - System Monitor
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10-bit, 1MSPS – Temperature and Voltage Monitor
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Zynq UltraScale+ MPSoC Device Selection Guide
Dimensions of FZ3 Card
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Software Features
The FZ3 Card is able to run PetaLinux 2020.1 and supports PaddlePaddle deep learning AI framework which is fully compatible to use Baidu Brain’s AI development tools like EasyDL, AI Studio and EasyEdge to enable developers and engineers to quickly leverage Baidu-proven technology or deploy self-defined models, enabling faster deployment.
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Item
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Features
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Description
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Source code provided
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Tool chains
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gcc8.3.0
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gcc version 8.3.0
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gcc 9.2.0
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aarch64-none-elf-gcc version 9.2.0
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Bootloader
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boot.bin
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First boot program including FSBL and u-boot2020.01
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Yes
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Linux Kernel
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Linux 5.4.0
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Customized kernel for FZ3 Card
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Yes
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USB2.0/3.0 Host
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USB2.0/3.0
Host driver
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Yes
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Ethernet
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Gigabit
Ethernet driver
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Yes
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MMC/SD/TF
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MMC/SD/TF
card driver
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Yes
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Qspi flash
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Qspi
flash driver
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Yes
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CAN
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CAN
driver
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Yes
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DP
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DP
driver
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Yes
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I2C
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I2C
driver
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Yes
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UART
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UART
driver
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Yes
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Watchdog
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Watchdog
driver
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Yes
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GPIO
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GPIO
driver
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Yes
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LED
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LED
driver
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Yes
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Button
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Button
driver
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Yes
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MIPI
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MIPI
camera driver
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Yes
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Application
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LED
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LED
example
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Yes
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CAN
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CAN
example
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Yes
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Net
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Socket
example
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Yes
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QT-Camera
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MIPI Camera example
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Yes
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File system
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Ramdisk
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Ramdisk
system image
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Rootfs
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Buildroot
making including Qt
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Yes
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Petalinux
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Petalinux2020.1
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Supports Xilinx Petalinux2020.1 development tools. MYIR provides
complete BSP for the FZ3 card.
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Software Features of Linux BSP
Baidu Brain’s AI development tools
Software Architecture of FZ3 Card
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Relative Download and Links
You can download relative chip datasheet, products datasheet, user manual, software package from below. Detailed technical data available on request.
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FZ3 Card
FZ3 Card with Installed Active Heatsink
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Price and Ordering
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Item
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Packing List
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Unit Price
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Ordering
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FZ3 Kit
(Part No.: MYS-ZU3EG-8E4D-EDGE-K2)
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- One
FZ3 Deep Learning Accelerator Card
(Installed
with active heatsink by default)
- One 12V/2A Power Adapter
- One
Mini USB Cable
- One
16GB TF Card
- One
Mini DP to HDMI Cable
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USD399
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FZ3 Card
(Part No.: MYS-ZU3EG-8E4D-EDGE)
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FZ3 Deep Learning Accelerator Card
(without any accessories)
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Production recommended
Please inquire MYIR
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Active heatsink for FZ3 Card
- 60mm * 52mm * 15mm
- aluminum heatsink with fan
- silicon pad
(Part No.: 2310100091/2310100065)
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USD19
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Note: Please contact MYIR to get development package (including documentations and software BSP) download link after placing your order.
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Overview
