All Projects → nvpro-samples → Optix_advanced_samples

nvpro-samples / Optix_advanced_samples

Programming Languages

c
50402 projects - #5 most used programming language

Labels

Projects that are alternatives of or similar to Optix advanced samples

cuda-toolkit
GitHub Action to install CUDA
Stars: ✭ 34 (-87.94%)
Mutual labels:  nvidia
xcloud-shield
Xcloud Beta Unofficial App for the Nvidia Shield Android TV. Playing Xbox Cloud Gaming directly on the box Nvidia Shield tv in the best way.
Stars: ✭ 93 (-67.02%)
Mutual labels:  nvidia
Torch-TensorRT
PyTorch/TorchScript compiler for NVIDIA GPUs using TensorRT
Stars: ✭ 1,216 (+331.21%)
Mutual labels:  nvidia
gpu-passthrough
A GPU passthrough tutorial using libvirt and KVM on GNU/Linux
Stars: ✭ 57 (-79.79%)
Mutual labels:  nvidia
SWARM
Profit Switching Mining Administrator For HiveOS/Linux & Windows: HiveOS Integrated
Stars: ✭ 66 (-76.6%)
Mutual labels:  nvidia
opencv-cuda-docker
Dockerfiles for OpenCV compiled with CUDA, opencv_contrib modules and Python 3 bindings
Stars: ✭ 55 (-80.5%)
Mutual labels:  nvidia
pycon-sg19-tensorflow-tutorial
PyCon SG 2019 Tutorial: Optimizing TensorFlow Performance
Stars: ✭ 26 (-90.78%)
Mutual labels:  nvidia
Gprmax
gprMax is open source software that simulates electromagnetic wave propagation using the Finite-Difference Time-Domain (FDTD) method for numerical modelling of Ground Penetrating Radar (GPR)
Stars: ✭ 268 (-4.96%)
Mutual labels:  nvidia
Dell-S2716DGR-Calibration-Guide
Calibration guide for the Dell S2716DG and S2716DGR to get the best picture quality and colors
Stars: ✭ 33 (-88.3%)
Mutual labels:  nvidia
GPU-Jupyterhub
Setting up a Jupyterhub Dockercontainer to spawn Jupyter Notebooks with GPU support (containing Tensorflow, Pytorch and Keras)
Stars: ✭ 23 (-91.84%)
Mutual labels:  nvidia
DistributedDeepLearning
Distributed Deep Learning using AzureML
Stars: ✭ 36 (-87.23%)
Mutual labels:  nvidia
Deep-Learning
It contains the coursework and the practice I have done while learning Deep Learning.🚀 👨‍💻💥 🚩🌈
Stars: ✭ 21 (-92.55%)
Mutual labels:  nvidia
a-minimalist-guide
Walkthroughs for DSL, AirSim, the Vector Institute, and more
Stars: ✭ 37 (-86.88%)
Mutual labels:  nvidia
kryptonite
Enable AMD/NVIDIA eGFX for All Thunderbolt Macs with SIP, ART & FileVault support.
Stars: ✭ 94 (-66.67%)
Mutual labels:  nvidia
Es Dev Stack
An on-premises, bare-metal solution for deploying GPU-powered applications in containers
Stars: ✭ 257 (-8.87%)
Mutual labels:  nvidia
zarch
The Ultimate Script For Arch Linux
Stars: ✭ 49 (-82.62%)
Mutual labels:  nvidia
vibrantLinux
A tool to automate managing your screen's saturation depending on what programs are running
Stars: ✭ 66 (-76.6%)
Mutual labels:  nvidia
Bmw Tensorflow Inference Api Gpu
This is a repository for an object detection inference API using the Tensorflow framework.
Stars: ✭ 277 (-1.77%)
Mutual labels:  nvidia
Clojurecl
ClojureCL is a Clojure library for parallel computations with OpenCL.
Stars: ✭ 266 (-5.67%)
Mutual labels:  nvidia
gpustats
Statistics on GPUs
Stars: ✭ 21 (-92.55%)
Mutual labels:  nvidia

OptiX Advanced Samples

Glass Ocean ProgressivePhotonMap Vox ParticleVolumes

This is a set of advanced samples for the NVIDIA OptiX Ray Tracing Engine. They assume some previous experience with OptiX and physically based rendering, unlike the basic tutorial-style samples in the SDK directory of the OptiX 4.0 distribution. They also use some different libraries than the SDK samples; GLFW and imgui in place of GLUT, for example. This means you cannot generally copy one of the advanced samples directly into the SDK, and vice versa.

Some samples, like optixVox and optixParticleVolumes, are new. Others used to ship in some form with OptiX prior to version 4.

Please navigate into the optixIntroduction sub-folder for specific documentation of the new tutorial examples contained inside that.

For requirements and build instructions see INSTALL-LINUX.txt or INSTALL-WIN.txt.

Technical support is available on NVIDIA's Developer Zone, or you can create a git issue.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].