GitCHN233/ml-suite

Getting Started with Xilinx ML Suite

Xilinx ML Suite v1.4

The Xilinx Machine Learning (ML) Suite provides users with the tools to develop and deploy Machine Learning applications for Real-time Inference. It provides support for many common machine learning frameworks such as Caffe, Tensorflow, and MXNet.

The ML Suite is composed of three basic parts:

1. ML Framework and Open Source Support - Support for high level ML Frameworks and other open source projects.
2. xfDNN Middleware - Software Library and Tools to Interface with ML Frameworks and optimize networks for Real-time Inference.
3. xDNN IP - High Performance CNN processing engine.

Learn More: ML Suite Overview
Watch: Webinar on Xilinx FPGA Accelerated Inference
Forum: ML Suite Forum

See What's New

• Release Notes
• Integration of Deephi DECENT Quantizer for Caffe
• xfDNN Runtime API upgraded to support multi-output networks
• XDNNv3 fully integrated for all platforms & models
• Ease of use enhancements
  • Docker Images
  • Run on FPGA using Caffe's custom Python layer
  • HDF5 format used for network weights

Getting Started

• Install XRT (Only necessary for On-Premise deployment)
• Start Docker Container
• Jupyter Notebook Tutorials
  • Caffe Image Classification
  • Caffe Object Detection w/ YOLOv2
• Command Line Examples
  • Caffe ImageNet Benchmark Models
  • Caffe VOC SSD Example
  • Deployment Mode Examples
• In-Browser GoogLeNet Demo
• REST Server Example
• Container Pipeline Example

References

• ML Suite Overview
• Performance Whitepaper
• Accuracy Benchmarks

System Requirements

Questions and Support

• FAQ
• ML Suite Forum
• AWS F1 Application Execution on Xilinx Virtex UltraScale Devices