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An implementation of NeRF acceleration using RTX cores to compute ray-grid intersections

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RTX NeRF

An implementation of NeRF acceleration using RTX cores to compute ray-grid intersections

Setup

Requirements

You will need:

  • a Nvidia GPU with compute capability>7.0 and driver version >=530.41.
  • Optix 7.7
  • CUDA
  • CMake > 3.18

Initial build and dependencies

In order to setup the repository, first download Optix. Then clone the repo. You'l first need to setup submodules.

git submodule init
git submodule update --init --recursive

If your Linux doesn't already have them installed install the following:

sudo apt-get install build-essential

We then need to build tiny-cuda-nn (this takes time)

cd lib/tiny-cuda-nn
mkdir build && cd build
cmake ..
make -j

Now that the tiny-cuda-nn static library is built we can compile the rtx_nerf project.

Navigate to the project root, and run the following:

mkdir build && cd build
cmake ../ -DOPTIX_HOME=[/path/to/optix/]
make

In order to build in debug mode

cmake ../ -DCMAKE_BUILD_TYPE=Debug -DOPTIX_HOME=[/path/to/optix/]
make

Running the executables

First download the data from the NeRF website. Then create a data folder and extract the data.

From the project root, run the executable

./build/bin/optx_nerf

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An implementation of NeRF acceleration using RTX cores to compute ray-grid intersections

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