Re-targetable interface for data exchange between heterogeneous systems and accelerator abstraction into software instructions

US11204747B1 · kind B1 · utility

Assignee

• XILINX, INC. · US

Inventors

• Jindrich Zejda · Saratoga, US
• Elliott Delaye · San Jose, US
• Yongjun Wu · Redmond, US
• Aaron Ng · San Jose, US
• Ashish Sirasao · San Jose, US
• Khang K. Dao · San Jose, US
• Christopher J. Case · San Francisco, US

Key dates

• Filing date: Oct 17, 2017
• Grant date: Dec 21, 2021
• Expiry date: Apr 7, 2039

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N3/063
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

Embodiments herein describe techniques for interfacing a neural network application with a neural network accelerator that operate on two heterogeneous computing systems. For example, the neural network application may execute on a central processing unit (CPU) in a computing system while the neural network accelerator executes on a FPGA. As a result, when moving a software-hardware boundary between the two heterogeneous systems, changes may be made to both the neural network application (using software code) and to the accelerator (using RTL). The embodiments herein describe a software defined approach where shared interface code is used to express both sides of the interface between the two heterogeneous systems in a single abstraction (e.g., a software class).