gmarkall / life-of-a-numba-kernelLinks
Worked example of the process from Python source to CUDA kernel execution with Numba
☆42Updated last year
Alternatives and similar repositories for life-of-a-numba-kernel
Users that are interested in life-of-a-numba-kernel are comparing it to the libraries listed below
Sorting:
- An Aspiring Drop-In Replacement for Pandas at Scale☆74Updated 4 years ago
- The Foundation for All Legate Libraries☆231Updated this week
- NPBench - A Benchmarking Suite for High-Performance NumPy☆89Updated last month
- A library that translates Python and NumPy to optimized distributed systems code.☆131Updated 3 years ago
- A stand-alone implementation of several NumPy dtype extensions used in machine learning.☆305Updated last week
- A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python☆333Updated last year
- No-GIL Python environment featuring NVIDIA Deep Learning libraries.☆68Updated 6 months ago
- Customized matrix multiplication kernels☆57Updated 3 years ago
- Sparsity support for PyTorch☆37Updated 7 months ago
- Einsum optimization using opt_einsum and PyTorch FX graph rewriting☆22Updated 3 years ago
- Automatically insert nvtx ranges to PyTorch models☆19Updated 4 years ago
- PyTorch interface for the IPU☆181Updated 2 years ago
- Collection of scripts to build PyTorch and the domain libraries from source.☆12Updated this week
- Material for the SC22 Deep Learning at Scale Tutorial☆41Updated 2 years ago
- Nvidia contributed CUDA tutorial for Numba☆262Updated 3 years ago
- ☆180Updated last year
- ☆53Updated last year
- The CUDA target for Numba☆207Updated last week
- Numbast is a tool to build an automated pipeline that converts CUDA APIs into Numba bindings.☆52Updated this week
- PyTorch RFCs (experimental)☆135Updated 5 months ago
- Documentation:☆125Updated 2 years ago
- CUDA templates for tile-sparse matrix multiplication based on CUTLASS.☆50Updated 7 years ago
- Dive into Jax, Flax, XLA and C++☆32Updated 5 years ago
- ☆16Updated last year
- Introduction to CUDA programming☆129Updated 8 years ago
- torch::deploy (multipy for non-torch uses) is a system that lets you get around the GIL problem by running multiple Python interpreters i…☆181Updated 2 months ago
- Example python package with pybind11 cpp extension☆57Updated 4 years ago
- A Deep Learning Meta-Framework and HPC Benchmarking Library☆81Updated 3 years ago
- ☆107Updated last year
- Material for the SC21 Deep Learning at Scale Tutorial☆27Updated 2 years ago