HIPRT-Path-Tracer

Overview

Physically based Monte Carlo path tracer written with the HIPRT and Orochi libraries.

HIPRT is AMD’s equivalent to OptiX. It allows the use of the ray tracing accelerators of RDNA2+ AMD GPUs and can run on NVIDIA devices as well (although it wouldn’t take advatange of RT cores) as it is not AMD specific.

The Orochi library allows the loading of HIP and CUDA libraries at runtime meaning that the application doesn’t have to be recompiled to be used on a GPU from a different vendor (unlike HIP which would require a recompilation + linking).

Features

Layered Principled BSDF:

Coat Microfacet GGX Layer + Anisotropy, Anisotropy Rotation, Medium Absorption & Thickness
On-the-fly Monte Carlo integration for energy compensation of interlayer clearcoat multiple scattering
SGGX Volumetric Sheen Lobe LTC Fit [Zeltner, Burley, Chiang, 2022]
Specular Microfacet GGX Layer
Oren-Nayar Diffuse BRDF Lobe
Metallic Microfacet GGX Layer + Anisotropy & Anisotropy Rotation + Double Roughness [Kulla & Conty, 2017]
Specular transmission BTDF + Beer Lambert Volumetric Absorption: [Burley, 2015]
Spectral dispersion using Cauchy’s equation
Multiple-scattering energy compensation for conductors (double metal layer), dielectrics (transmission layer) and glossy-diffuse (specular + diffuse layer) materials [Turquin, 2019]
Thin-film interference over dielectrics and conductors [Belcour, Barla, 2017]
Thin-walled model

Sampling

Light sampling:
- Uniform light sampling for direct lighting estimation + MIS
- Resampled Importance Sampling (RIS) [Talbot et al., 2005]+ Weighted Reservoir Sampling (WRS) for many light sampling + [M. T. Chao, 1982]
- ReSTIR DI [Bitterli et al., 2020]
  - Supports envmap sampling
  - Many bias correction weighting schemes for experimentations (1/M, 1/Z, MIS-like, Generalized Balance Heuristic, Pairwise MIS [Bitterli, 2022], Pairwise MIS with defensive formulation [Lin et al., 2022])
  - Fused Spatiotemporal Reuse [Wyman, Panteleev, 2021]
  - Light Presampling [Wyman, Panteleev, 2021]
- HDR Environment map + Multiple Importance Sampling using
  - CDF-inversion & binary search
  - Alias Table (Vose’s O(N) construction [Vose, 1991])
BSDF sampling:
- MIS
- Smith GGX Sampling:
  - Visible Normal Distribution Function (VNDF) [Heitz, 2018]
  - Spherical caps VNDF Sampling [Dupuy, Benyoub, 2023]

Other rendering features:

Texture support for all the parameters of the BSDF
Texture alpha transparency support
Stochastic material opacity support
Normal mapping
Nested dielectrics support
- Automatic handling as presented in [Ray Tracing Gems, 2019]
- Handling with priorities as proposed in [Simple Nested Dielectrics in Ray Traced Images, Schmidt, 2002]
Per-pixel adaptive sampling
Intel Open Image Denoise + Normals & Albedo AOV support

UI

Interactive ImGui interface
- Asynchronous interface to guarantee smooth UI interactions even with heavy path tracing kernels
Interactive first-person camera
Different frame-buffer visualization (visualize the adaptive sampling heatmap, the denoiser normals / albedo, …)

Other features

Use of the [ASSIMP] library to support many scene file formats.
Multithreaded scene parsing/texture loading/shader compiling/BVH building/envmap processing/… for faster application startup times
Background-asynchronous path tracing kernels pre-compilation
Shader cache to avoid recompiling kernels unnecessarily