Simple tests for JAX, PyTorch, and TensorFlow to test if the installed NVIDIA drivers are being properly picked up
MIT License
Published by matthewfeickert about 3 years ago
Instructions tested with nvidia-driver-455.
nvidia-driver-455
Object detection for video surveillance
Dockerfiles and manual for easy build of docker image with CUDA10.X and cuDNN7.6 to run TensorFlo...
Provide Docker build sequences of Open3D for various environments.
Matrix multiplication example performed with OpenMP, OpenACC, BLAS, cuBLABS, and CUDA
SDK for GPU accelerated genome assembly and analysis
GitHub Action to install CUDA
Provides an environment for compiling TensorFlow or PyTorch with CUDA for aarch64 on an x86 machi...
CUDA C++ Core Libraries
Performance-optimized wheels for TensorFlow (SSE, AVX, FMA, XLA, MPI)
3D Gaussian Splatting, reimagined: Unleashing unmatched speed with C++ and CUDA from the ground up!
A nvImageCodec library of GPU- and CPU- accelerated codecs featuring a unified interface
Fast, reproducible, and portable software development environments
Solvers/annealers for simulated quantum annealing on CPU and CUDA(NVIDIA GPU).
Provide Docker build sequences of PyTorch for various environments.
BQN virtual machine