The Zynq™ 7000 SoC ZC706 Evaluation Kit includes all the basic components of hardware, design tools, IP etc.
Please consider the PicoZed as an alternative.
The Zynq™ 7000 SoC ZC706 Evaluation Kit includes all the basic components of hardware, design tools, IP, and pre-verified reference designs including a targeted design, enabling a complete embedded processing platform and transceiver based designs including PCIe. The included pre-verified reference designs and industry-standard FPGA Mezzanine Connectors (FMC) allow scaling and customization with daughter cards. Please check the PetaLinux Software Development Kit page for information on the AMD processing systems.
Featuring the ROHS compliant ZC706 including the XC7Z045 FFG900 – 2 SoC
Logic Cells | 350 |
---|---|
Block RAM (Mb) | 19.1 |
DSP Slices | 900 |
Maximum I/O Pins | 362 |
Maximum Transceiver Count | 16 |
Featuring the ZC706 Evaluation Board
Communication & Networking
Expansion Connectors
Control & I/O
Clocking
Configuration
Memory
Analog
Power
Featuring the XC7Z045 FFG900 -2 SoC
Node locked & Device-locked to the Zynq 7000 XC7Z045 SoC, with 1 year of updates
Name | Description | License Type | Files |
---|---|---|---|
Vivado Design Suite | The AMD Vivado™ Design Suite is a revolutionary IP and System Centric design environment built from the ground up to accelerate the design for FPGAs and SoCs. | Node locked and device-locked to the XCZU7EV MPSoC FPGA, with one year of updates | Download Vivado Design Suite |
Vitis Unified Software Platform | Full suite of tools for embedded software development, hardware acceleration, and debug targeting AMD platforms. | Free | Download Vitis Embedded Platforms |
PetaLinux Tools | Configure, Build, and Deploy Linux operating system to AMD platforms. | Free | Download Petalinux Tools |
Name | Product Category | Item | Description |
---|---|---|---|
Deep Learning HDL Toolbox | Support Package | MathWorks | Enables deployment of deep learning processors on AMD FPGAs and SOCs using MATLAB |
Getting Started Guide for Deep Learning HDL Toolbox | Training |
MathWorks | Learn how to create, compile, and deploy a dlhdl.workflow object using Deep Learning HDL Toolbox™ Support Package. |