MYS-ZU3EG-8E4D-EDGE-K2 이미지 확대 보기
  • MYS-ZU3EG-8E4D-EDGE-K2
  • MYS-ZU3EG-8E4D-EDGE-K2

MYS-ZU3EG-8E4D-EDGE-K2

공유
짧은설명
FZ3 Card - Deep Learning Accelerator Card
판매가
591,800 <관세ㆍ부가세 포함>
구매제한
옵션당 최소 1개
구매혜택
할인 : 적립 마일리지 :
배송비
44,000원
택배
방문 수령지 : 경기도 성남시 중원구 사기막골로 99 성남센트럴비즈타워2차 B동 913호
상품코드
1000618295
제조사
MYIR Tech

상품상세정보

- 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 

 

Overview

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.

 

1FZ3 Card Overview901 KB
2Zynq UltraScale+ MPSoC Product Selection Guide1.88 MB
3MYC-CZU3EG CPU Module Overview
1.00 MB
4FZ3 Card Expansion Connector Pinouts Description45.3 KB

 

배송안내

 결제일로부터 1~3주 안에 배송됩니다.

 제조사 재고가 부족하여 3주 안에 배송이 어려울 경우 메일로 안내해 드리니 참고하시기 바랍니다.

교환 및 반품안내

 본 상품은 해외 재고 상품으로 기본적으로 교환 및 반품 처리가 어렵습니다.

 상품에 따라 교환 및 반품 처리가 가능한 경우 비용이 수반되며 이니프로 고객센터에 연락하여 처리하시기 바랍니다.

환불안내

 본 상품은 해외 재고 상품으로 기본적으로 환불 처리가 어렵습니다.

 상품에 따라 환불이 가능한 경우 비용이 수반되며 이니프로 고객센터에 연락하여 처리하시기 바랍니다.

AS안내

 제조사별로 A/S정책이 상이하니 하단 고객센터로 문의 주시기 바랍니다. 

이미지 확대보기MYS-ZU3EG-8E4D-EDGE-K2

MYS-ZU3EG-8E4D-EDGE-K2
  • MYS-ZU3EG-8E4D-EDGE-K2
  • MYS-ZU3EG-8E4D-EDGE-K2
닫기

비밀번호 인증

글 작성시 설정한 비밀번호를 입력해 주세요.

닫기

장바구니 담기

상품이 장바구니에 담겼습니다.
바로 확인하시겠습니까?

찜 리스트 담기

상품이 찜 리스트에 담겼습니다.
바로 확인하시겠습니까?

상단으로 이동