Invention Grant
- Patent Title: Learning neural networks of programmable device blocks directly with backpropagation
-
Application No.: US16449264Application Date: 2019-06-21
-
Publication No.: US12067484B2Publication Date: 2024-08-20
- Inventor: Yaman Umuroglu , Nicholas Fraser , Michaela Blott , Kristof Denolf , Kornelis A. Vissers
- Applicant: Xilinx, Inc.
- Applicant Address: US CA San Jose
- Assignee: XILINX, INC.
- Current Assignee: XILINX, INC.
- Current Assignee Address: US CA San Jose
- Agency: Patterson + Sheridan, LLP
- Main IPC: G06N3/063
- IPC: G06N3/063 ; G06N3/08 ; G06N3/082 ; G06N3/084
Abstract:
An example method of training a neural network includes defining hardware building blocks (HBBs), neuron equivalents (NEQs), and conversion procedures from NEQs to HBBs; defining the neural network using the NEQs in a machine learning framework; training the neural network on a training platform; and converting the neural network as trained into a netlist of HBBs using the conversion procedures to convert the NEQs in the neural network to the HBBs of the netlist.
Information query
