shlean / ml-suite

Getting Started with Xilinx ML Suite

Xilinx ML Suite

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, MxNet and Tensorflow as well as Python and RESTful APIs.

The ML Suite is composed of three basic parts:

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

Get familiar with the ML Suite Here

Getting Started

1. Install Anaconda2.
2. Install git lfs
3. Clone this repo
   git clone https://github.com/Xilinx/ml-suite.git

If you are using the AWS EC2 F1 FPGA DEVELOPER AMI the following steps are necessary to setup the drivers:

1. git clone https://github.com/aws/aws-fpga.git
2. cd aws-fpga
3. source sdaccel_setup.sh

Once your environment is set up, take a look at some of the command line tutorials and Jupyter Notebooks here:

• Tutorials

Minimum System Requirements

• OS: Ubuntu 16.04.2 LTS, CentOS
• CPU: 4 Cores (Intel/AMD)
• Memory: 8 GB

Supported Platforms

Cloud Services

• Amazon AWS EC2 F1
• Nimbix

On Premise Platforms

• Xilinx Virtex UltraScale+ FPGA VCU1525 Acceleration Development Kit
  • Note: The xilinx_vcu1525_dynamic_5_1 DSA is required to be installed. Installation information can be found on page 118 of UG1023

Release Notes

• 1.0
• 1.1

Questions and Support

• FAQ
• AWS F1 Application Execution on Xilinx Virtex UltraScale Devices
• SDAccel Forums