numba / nvidia-cuda-tutorialLinks
Nvidia contributed CUDA tutorial for Numba
☆262Updated 3 years ago
Alternatives and similar repositories for nvidia-cuda-tutorial
Users that are interested in nvidia-cuda-tutorial are comparing it to the libraries listed below
Sorting:
- The Foundation for All Legate Libraries☆233Updated this week
- A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python☆333Updated last year
- GPU Development in Python 101 tutorial☆278Updated last year
- Numba tutorial for GTC2019☆134Updated 2 years ago
- Python in High Performance Computing☆365Updated 9 months ago
- The CUDA target for Numba☆222Updated this week
- An Aspiring Drop-In Replacement for Pandas at Scale☆74Updated 4 years ago
- Worked example of the process from Python source to CUDA kernel execution with Numba☆44Updated last year
- scikit-learn_bench benchmarks various implementations of machine learning algorithms across data analytics frameworks. It currently suppo…☆118Updated this week
- Crash course to master gradient-based machine learning. Also secretly a JAX course in disguise!☆231Updated last year
- Drop-in autodiff for NumPy.☆213Updated 2 weeks ago
- RFC document, tooling and other content related to the array API standard☆261Updated 3 weeks ago
- Example Numba implementations of functions☆178Updated 3 years ago
- PythonHPC☆115Updated 2 years ago
- Utilities for Dask and CUDA interactions☆318Updated last week
- DeepHyper: A Python Package for Massively Parallel Hyperparameter Optimization in Machine Learning☆302Updated last week
- Create Numpy .npy files by appending on the growth axis☆65Updated 5 months ago
- Notebooks for the "Deep Learning with JAX" book☆162Updated 6 months ago
- Material for the SC21 Deep Learning at Scale Tutorial☆27Updated 2 years ago
- A library that translates Python and NumPy to optimized distributed systems code.☆131Updated 3 years ago
- Neural Networks library in pure numpy☆70Updated last year
- NVIDIA Math Libraries for the Python Ecosystem☆537Updated 3 weeks ago
- A stand-alone implementation of several NumPy dtype extensions used in machine learning.☆315Updated last week
- NumPy and SciPy on Multi-Node Multi-GPU systems☆959Updated this week
- Parallel Hyperparameter Tuning in Python☆417Updated 9 months ago
- Exploring using stdpar and Cython☆34Updated 5 years ago
- Productionize machine learning predictions, with ONNX or without☆66Updated last year
- torch::deploy (multipy for non-torch uses) is a system that lets you get around the GIL problem by running multiple Python interpreters i…☆182Updated 3 months ago
- FasterAI: Prune and Distill your models with FastAI and PyTorch☆250Updated last month
- A Pytree Module system for Deep Learning in JAX☆214Updated 2 years ago