VTA: Deep Learning Accelerator Stack¶
The Versatile Tensor Accelerator (VTA) is an open, generic, and customizable deep learning accelerator with a complete TVM-based compiler stack. We designed VTA to expose the most salient and common characteristics of mainstream deep learning accelerators. Together TVM and VTA form an end-to-end hardware-software deep learning system stack that includes hardware design, drivers, a JIT runtime, and an optimizing compiler stack based on TVM.
VTA has the following key features:
- Generic, modular, open-source hardware.
- Streamlined workflow to deploy to FPGAs.
- Simulator support to prototype compilation passes on regular workstations.
- Pynq-based driver and JIT runtime for both simulated and FPGA hardware back-end.
- End to end TVM stack integration.
This page contains links to all the resources related to VTA: