Vitis In-Depth Tutorials

Port fpga-zynq (rocket-chip) to Xilinx ZYNQ Ultrascale+ board (ZCU102)

A portable interface for energy monitoring utilities

Workflow for Executing CNN Networks on Zynq Ultrascale+ with VITIS AI. Detailed analysis, configuration, and execution of Convolutional Neural Networks on ZCU102 using VITIS AI, evaluating performance on the board compared to Cloud infrastructure. Developed for educational exam purposes.

ZCU102 two IMX274 camera design.

Generate and install boot apps for the Zynq MPSoC device

Collection of FPGA modules for video capture and processing.

This repository contains the source code for implementing data exchange through the SFP+ Cages of the Xilinx's Multi-processor System-on-Chip (MPSoC)

Xilinx Vitis repository containing video streaming and machine learning reference designs.

Workflow for executing CNN Networks on Zynq Ultrascale+ with Vitis AI toolchain. Detailed analysis, configuration and execution of Convolutional Neural Networks on ZCU102 using Vitis AI, evaluating performance on the board compared to Cloud infrastructure (eg. Kaggle). Developed for educational exam purposes.

✅ The testing program validates the BlueDBM flashboard for the ZCU102 motherboard.

This directory contains the source code for implementing Random Linear Network Coding (RLNC) into Multi-Processor System-on-Chips (MPSoC). By exploiting data vectorization, we obtained latency and throughputs gains during the matrix multiplication operations.