dionhaefner / pyhpc-benchmarksLinks
A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python
☆331Updated 11 months ago
Alternatives and similar repositories for pyhpc-benchmarks
Users that are interested in pyhpc-benchmarks are comparing it to the libraries listed below
Sorting:
- Zero-copy MPI communication of JAX arrays, for turbo-charged HPC applications in Python☆492Updated 3 weeks ago
- RFC document, tooling and other content related to the array API standard☆252Updated last week
- An Aspiring Drop-In Replacement for Pandas at Scale☆74Updated 3 years ago
- Extending JAX with custom C++ and CUDA code☆398Updated last year
- Drop-in autodiff for NumPy.☆213Updated last week
- The Foundation for All Legate Libraries☆225Updated this week
- A library that translates Python and NumPy to optimized distributed systems code.☆132Updated 2 years ago
- Machine Learning for HPC Workflows☆141Updated this week
- Python helpers to limit the number of threads used in native libraries that handle their own internal threadpool (BLAS and OpenMP impleme…☆393Updated 4 months ago
- Example python (numpy) -- CUDA installable package with a C-extension library☆143Updated 6 years ago
- DeepHyper: A Python Package for Massively Parallel Hyperparameter Optimization in Machine Learning☆296Updated this week
- Mathematical operations for JAX pytrees☆200Updated 9 months ago
- ⚡️Optimizing einsum functions in NumPy, Tensorflow, Dask, and more with contraction order optimization.☆939Updated 3 months ago
- Distributed tensors and Machine Learning framework with GPU and MPI acceleration in Python☆223Updated last week
- Automatic parallelization of Python/NumPy, C, and C++ codes on Linux and MacOSX☆221Updated 4 years ago
- Turn SymPy expressions into trainable JAX expressions.☆349Updated 4 months ago
- Data Parallel Extension for Numba☆83Updated 9 months ago
- Documentation:☆121Updated 2 years ago
- Example Numba implementations of functions☆176Updated 2 years ago
- NPBench - A Benchmarking Suite for High-Performance NumPy☆87Updated 3 months ago
- NVIDIA Math Libraries for the Python Ecosystem☆350Updated last week
- A simple Python wrapper for Slurm with flexibility in mind.☆154Updated 4 months ago
- Parallel NumPy seamlessly speeds up NumPy for large arrays (64K+ elements) with no change required to existing code.☆63Updated 4 years ago
- Worked example of the process from Python source to CUDA kernel execution with Numba☆41Updated last year
- Make your Python code fly at transonic speeds!☆125Updated this week
- Numba tutorial for GTC2019☆134Updated 2 years ago
- Sparse multi-dimensional arrays for the PyData ecosystem☆645Updated this week
- Analyze graph/hierarchical performance data using pandas dataframes☆116Updated 7 months ago
- Accurate sums and dot products for Python.☆106Updated 4 years ago
- Stencil computations in JAX☆71Updated last year