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Development Environment

Xilinx SDSoC (1)

HMI Solutions

MYD-Y6ULX-CHMI (i.MX 6UL/6ULL) (1)

MY-EVC5100S-HMI (TI AM335x) (1)

Single Board Computers

MYS-6ULX (NXP i.MX 6UL/6ULL) (2)

Rico Board (TI AM437x) (1)

FZ3 Card (Xilinx ZU3EG) (1)

Z-turn Board (Xilinx Zynq-7010/20) (1)

Z-turn Lite (Xilinx Z-7007S/7010) (1)

MYS-SAM9X5 (Atmel SAM9X5) (1)

MYS-SAM9G45 (Atmel SAM9G45) (1)

MYS-S5PV210 (Samsung S5PV210) (1)

CPU Modules

MYC-CZU3EG/4EV (ZU3EG/4EV) (1)

MYC-Y7Z010/20 (Zynq-7010/20) (1)

MYC-C7Z010/20 (Zynq-7010/20) (1)

MYC-C7Z015 (Xilinx Zynq-7015) (1)

MYC-YA157C (ST STM32MP157A) (1)

MYC-C8MMX (NXP i.MX 8M Mini) (1)

MYC-JX8MX (NXP i.MX8M) (1)

MYC-Y6ULX (NXP i.MX 6UL/6ULL) (1)

MYC-IMX28X (NXP i.MX28) (1)

MYC-C335X-GW (TI AM335x) (1)

MCC-AM335X-Y (TI AM335x) (1)

MYC-AM335X (TI AM335x) (1)

MCC-AM335X-J (TI AM335x) (1)

MYC-C437X (TI AM437x) (1)

MYC-SAMA5D3X (Atmel A5D3) (1)

MYC-JA5D4X (Atmel A5D4) (1)

MYC-JA5D2X (Atmel A5D2) (1)

MCC-SAMA5D3X-C (Atmel A5D3) (1)

MYC-SAM9X5 (Atmel SAM9X5) (1)

MYC-SAM9X5-V2 (Atmel SAM9X5) (1)

MYC-S5PV210 (Samsung S5PV210) (1)

MYC-Exynos4412 (Samsung) (1)

Development Boards

VECP Starter Kit (Xilinx ZU3EG) (1)

MYD-CZU3EG/4EV (ZU3EG/4EV) (1)

MYD-C7Z010/20 (Zynq-7010/20) (1)

MYD-Y7Z010/20 (Zynq-7010/20) (1)

MYD-C7Z015 (Xilinx Zynq-7015) (1)

MYD-IMX28X (NXP i.MX28) (1)

MYD-YA157C (ST STM32MP157A) (1)

MYD-Y6ULX (NXP i.MX 6UL/6ULL) (1)

MYD-JX8MX (NXP i.MX8M) (1)

MYD-C8MMX (NXP i.MX 8M Mini) (1)

MYD-Y6ULX-HMI (i.MX 6UL/6ULL) (1)

MYD-C335X-GW (TI AM335x) (1)

MYD-C437X (TI AM437x) (1)

MYD-AM335X-Y (TI AM335x) (1)

MYD-AM335X-J (TI AM335x) (1)

MYD-AM335X (TI AM335x) (1)

MYD-C437X-PRU (TI AM437x) (1)

MYD-JA5D4X (Atmel A5D4) (1)

MYD-SAMA5D3X-C (Atmel A5D3) (1)

MYD-SAMA5D3X (Atmel A5D3) (1)

MYD-JA5D2X (Atmel A5D2) (1)

MYD-SAM9X5 (Atmel SAM9X5) (1)

MYD-SAM9X5-V2 (Atmel SAM9X5) (1)

MYD-LPC185X (NXP LPC185x) (2)

MYD-LPC435X (NXP LPC435x) (2)

MYD-LPC1788 (NXP LPC1788) (1)

Add-on Options

Z-turn IO Cape (for Z-turn Board) (1)

Z-turn Lite IO Cape (for Z-turn Lite) (1)

MYD-Y7Z010/20 IO Cape (1)

MYB-Y6ULX-HMI-4GEXP (1)

MYB-6ULX (for MYS-6ULX) (1)

MY-LCD43TP LCD Module (1)

MY-LCD70TP LCD Module (1)

MY-LCD70TP-C LCD Module (1)

MY-LVDS070C LCD Module (1)

MY-WF003U USB WiFi Module (1)

MY-WF004S SDIO WiFi Module (1)

MY-CAM002U Camera Module (1)

MY-CAM011B BUS Camera Module (1)

MY-UART012U Convertor (1)

MY-CAM003M Camera Module (1)

MY-SODIMM200 Socket (1)

MY-ZB010C ZigBee Module (1)

MY-ZB010C-E ZigBee EVM (1)

    Product Updates
          Products >  Single Board Computers >  FZ3 Card (Xilinx ZU3EG) > FZ3 Card - Deep Learning Accelerator Card
 
FZ3 Card - Deep Learning Accelerator Card

FZ3 Card - Deep Learning Accelerator Card

- Xilinx Zynq UltraScale+ ZU3EG MPSoC based on 1.2 GHz Quad Arm Cortex-A53 and 600MHz Dual Cortex-M4 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
- Supports Baidu's PaddlePaddle Deep Learning AI Framework
 

MYIR is a Xilinx Alliance Member, welcome to use MYIR's Xilinx products!
We also offer custom design services, welcome your inquiry!

http://www.xilinx.com/alliance/memberlocator/1-2wv1bc.html


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 2019.1 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. 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.




Features


Description

Dimensions


100mm x 70mm

PCB Layer


12-layer

Power Supply


DC12V/2A

Static Power


About 5W

Working Temp.


-40°C~85°C

Target Applications


AI Camera, AI Computing Box, AI Robot, Smart Car, Intelligent Electronic Scale, Patrol UAV, etc.

CPU


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

RAM


4GB DDR4 (64-bit)

Flash


8GB eMMC, 32MB QSPI, 32KB EEPROM

Ethernet


1 x Gigabit Ethernet

USB


1 x USB 2.0 Host, 1 x USB 3.0 Host

TF Card


1 x Micro SD Card Slot

DP


1 x Mini DisplayPort (4K/30fps, 2-lane)

PCIe


1 x PCIe 2.1 Interface (1-lane)

MIPI-CSI


1 x MIPI-CSI Interface (25-pin 0.3mm pitch FPC connector)

BT1120


1 x BT1120 Camera Interface (32-pin 0.5mm pitch FPC connector)

Debug


1 x Mini USB-to-UART Port

JTAG


1 x 6-pin 2.54mm pitch pin header

LED

1 x Power LED, 4 x Status LEDs (2 x Red, 2 x Green)

Buttons


1 x FPGA Reset Button, 1 x System Reset Button

Others


1 x RTC Battery Socket (AG2 or LR41 battery is recommended)

Expansion IOs


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.

Software


Ready to run PetaLinux, supports PaddlePaddle deep learning AI framework

Features of FZ3 Card


FZ3 Card in the Video

FZ3 deep learning accelerator card based on Xilinx Zynq UltraScale+ ZU3EG



Other MYIR's Xilinx Products

http://www.myirtech.com/xilinxseries.asp

Z-turn Board Single Board Computer (based on Zynq-7010 / 7020)

Z-turn Lite Single Board Computer (based on Zynq-7007S / Zynq-7010)

MYD-C7Z015 Development Board (MYC-C7Z015 CPU Module as core board)

MYD-Y7Z010/20 Development Board (MYC-Y7Z010/20 CPU Module as core board)

MYD-C7Z010/20 Development Board (MYC-C7Z010/20 CPU Module as core board)

MYD-CZU3EG Development Board (MYC-CZU3EG CPU Module as core board)

MYD-CZU4EV Development Board (MYC-CZU4EV CPU Module as core board)

VECP Starter Kit - a complete Vision Edge Computing Platform (based on Xilinx Zynq UltraScale+ ZU3EG MPSoC)




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.

Device

XCZU2CG

XCZU3CG

XCZU3EG

XCZU4EV

XCZU5EV

Logic cells (k)

103

154

154

192

256

CLB Flip-Flops (K)

94

141

141

176

234

CLB LUTs (K)

47

71

71

88

117

Block RAM (Mb)

5.3

7.6

7.6

4.5

5.1

UltraRAM (Mb)

-

-

-

13.5

18.0

DSP Slices

240

360

360

728

1,248

GTX transceivers

PS-GTR4x (6Gb/s)

PS-GTR4x (6Gb/s)

PS-GTR4x (6Gb/s)

PS-GTR4x (6Gb/s), GTH4x (16.3Gb/s)

PS-GTR4x (6Gb/s), GTH4x (16.3Gb/s)

Processor Units

Application Processor Unit

Dual-core ARM® Cortex™-A53 MPCore™ up to 1.3GHz

Quad-core ARM® Cortex™-A53 MPCore™ up to 1.5GHz

Memory w/ECC

L1 Cache 32KB I / D per core, L2 Cache 1MB, on-chip Memory 256KB

Real-Time Processor Unit

Dual-core ARM Cortex-R5 MPCore™ up to 600MHz

Memory w/ECC

L1 Cache 32KB I / D per core, Tightly Coupled Memory 128KB per core

Graphics Processing Unit

-

-

Mali™-400 MP2 up to 667MHz

Video Codec

-

-

-

H.264 / H.265

Memory L2 Cache

64KB

External Memory, Connectivity, Integrated Block Functionality

Dynamic Memory Interface

x32/x64: DDR4, LPDDR4, DDR3, DDR3L, LPDDR3 with ECC

Static Memory Interfaces

NAND, 2x Quad-SPI

High-Speed Connectivity

PCIe® Gen2 x4, 2x USB3.0, SATA 3.1, DisplayPort, 4x Tri-mode Gigabit Ethernet

General Connectivity

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

Power Management

Full / Low / PL / Battery Power Domains

Security

RSA, AES, and SHA

AMS - System Monitor

10-bit, 1MSPS – Temperature and Voltage Monitor


Zynq UltraScale+ MPSoC Device Selection Guide



Dimensions of FZ3 Card






Software Features

The FZ3 Card is able to run PetaLinux 2019.1 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.


Baidu Brain’s AI development tools


Software Architecture of FZ3 Card







Relative Download and Links


You can download relative chip datasheet, products datasheet, user manual, software package from below. Detailed technical data available on request.


1 FZ3 Card Overview 901 KB
2 Zynq UltraScale+ MPSoC Product Selection Guide 1.88 MB
3 MYC-CZU3EG CPU Module Overview
1.00 MB
4 FZ3 Card Expansion Connector Pinouts Description 45.3 KB
5 FZ3 Deep Learning Accelerator Card Hardware Manual
3.64 MB
6 FZ3 Deep Learning Accelerator Card User Manual V1.0.0
1.97 MB
7 FZ3 Card Schematic 1.27 MB

FZ3 Card


FZ3 Card with Installed Active Heatsink







Price and Ordering

Item

Packing List

Unit Price

Ordering

FZ3 Kit

(Part No.: MYS-ZU3EG-8E4D-EDGE-K2)

- 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

USD259

FZ3 Card
(Part No.: MYS-ZU3EG-8E4D-EDGE)

FZ3 Deep Learning Accelerator Card

(without any accessories)

Production recommended
Please inquire MYIR
Active heatsink for FZ3 Card
- 60mm * 52mm * 15mm
- aluminum heatsink with fan
- silicon pad

(Part No.: 2310100091/2310100065)


USD19

Note: Please contact MYIR to get development package (including documentations and software BSP) download link after placing your order.







 

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