nvdla学习笔记_NVDLA: NVDLA ，即 NVIDIA Deep Learning Accelerator ，是英伟达开源的一个开放框架，以促进设计深度学习推断加速的标准方法...

NVDLA Open Source Hardware

NVDLA

The NVIDIA Deep Learning Accelerator (NVDLA) is a free and open architecture that promotes

a standard way to design deep learning inference accelerators. With its modular architecture,

NVDLA is scalable, highly configurable, and designed to simplify integration and portability.

Learn more about NVDLA on the project web page.

Online Documentation

NVDLA documentation is located here. Hardware specific

documentation is located at the following pages.

This README file contains only basic information.

Directory Structure

This repository contains the RTL, C-model, and testbench code associated with the NVDLA hardware

release. In this repository, you will find:

vmod/ -- RTL model, including:

vmod/nvdla/ -- Verilog implementation of NVDLA

vmod/vlibs/ -- library and cell models

vmod/rams/ -- behavioral models of RAMs used by NVDLA

syn/ -- example synthesis scripts for NVDLA

perf/ -- performance estimator spreadsheet for NVDLA

verif/ -- trace-player testbench for basic sanity validation

verif/traces/ -- sample traces associated with various networks

tools -- tools used for building the RTL and running simulation/synthesis/etc.

spec -- RTL configuration option settings.

Building the NVDLA Hardware

See the integrator's manual for more information on

the setup and other build commands and options. The basic build command to compile the design

and run a short sanity simulation is:

bin/tmake