MYS-ZU3EG-8E4D-EDGE-K2

Microcontrollers, Microprocessor, FPGA Modules Overview

The MYIR MYS-ZU3EG-8E4D-EDGE-K2 is a deep learning accelerator kit based on the Xilinx Zynq UltraScale+ XCZU3EG MPSoC. It features a quad-core ARM Cortex-A53 processor running at 1.2 GHz and a dual-core Cortex-R5 real-time processor at 600 MHz. The system integrates 4GB of 64-bit DDR4 SDRAM (2400MHz), 8GB eMMC, and 32MB QSPI Flash. Hardware interfaces include USB 3.0, Gigabit Ethernet, PCIe Gen2 x1, Mini DisplayPort, MIPI-CSI, and BT1120 camera inputs. The kit supports PetaLinux 2020.1 and the PaddlePaddle AI framework.

Microcontrollers, Microprocessor, FPGA Modules Feature Summary

• Xilinx Zynq UltraScale+ XCZU3EG-1SFVC784I SoC with 1.2GHz Quad-Core A53 and 600MHz Dual-Core R5
• 4GB DDR4 SDRAM (64-bit, 2400MHz) and 8GB eMMC storage
• Supports PetaLinux 2020.1 BSP and Baidu PaddlePaddle deep learning framework
• Includes MIPI-CSI and BT1120 camera interfaces for vision applications

Microcontrollers, Microprocessor, FPGA Modules Applications

• AI Camera systems
• AI Computing Box / Edge devices
• Intelligent Robotics
• Smart Car / ADAS
• Patrol UAVs

Microcontrollers, Microprocessor, FPGA Modules Procurement Notes

This part number represents the FZ3 Kit bundle, which includes the FZ3 Card with an installed active heatsink, a 12V/2A power adapter, a mini USB cable, a 16GB TF card, and a mini DP to HDMI cable. Contact MYIR Electronics directly after ordering to obtain download links for development resources, documentation, and software BSPs.

Microcontrollers, Microprocessor, FPGA Modules Selection Notes

Select this model when a complete out-of-the-box evaluation environment is required for the ZU3EG MPSoC. The kit provides necessary accessories for immediate deployment. For standalone module integration without accessories, consider the base card part number MYS-ZU3EG-8E4D-EDGE. Ensure compatibility with the 12V/2A DC power supply requirement.

Microcontrollers, Microprocessor, FPGA Modules Part Context

The MYS-ZU3EG-8E4D-EDGE-K2 is the packaged kit version of the FZ3 Deep Learning Accelerator Card. It utilizes the XCZU3EG-1SFVC784I chip, which offers footprint compatibility with other Zynq UltraScale+ variants like the CG and EV series, allowing for potential future migration within the same package size.

Microcontrollers, Microprocessor, FPGA Modules Replacement Considerations

For standalone board replacement, use part number MYS-ZU3EG-8E4D-EDGE. For device migration within the same package, compatible chips include XCZU2CG, XCZU3CG, XCZU4EV, and XCZU5EV, though logic and memory resources vary significantly between these models.

Microcontrollers, Microprocessor, FPGA Modules FAQ

What AI frameworks are supported by the FZ3 Card?

The FZ3 Card supports the Xilinx Vitis Software Development Platform and Baidu’s PaddlePaddle deep learning AI framework. It is compatible with Baidu Brain tools such as EasyDL, AI Studio, and EasyEdge.

Does the MYS-ZU3EG-8E4D-EDGE-K2 include a camera?

No, the kit does not include a camera module. However, the FZ3 Card hardware supports camera input via one MIPI-CSI interface (FPC_25PIN 4-lane) and one BT1120 interface (FPC_32PIN 16-bit).

What is the operating temperature range of the FZ3 Card?

The specified working temperature range for the FZ3 Card is -45°C to 85°C.