Computing with Python functions.

A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner

Evolutionary algorithm toolbox and framework with high performance for Python

📈 Adaptive: parallel active learning of mathematical functions

OpenCL integration for Python, plus shiny features

Python bindings for MPI

Numba extension for compiling Pandas data frames, Intel® Scalable Dataframe Compiler

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.

Zero-copy MPI communication of JAX arrays, for turbo-charged HPC applications in Python ⚡

Parallel programming with Python

A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python 🚀

Comfortable parallel TQDM using concurrent.futures

PyTorch implementation of Soft-Actor-Critic and Prioritized Experience Replay (PER) + Emphasizing Recent Experience (ERE) + Munchausen RL + D2RL and parallel Environments.

Distributed and Parallel Computing Framework with / for Python

optimagic is a Python package for numerical optimization. It is a unified interface to optimizers from SciPy, NlOpt and other packages. optimagic's minimize function works just like SciPy's, so you don't have to adjust your code. You simply get more optimizers for free. On top you get diagnostic tools, parallel numerical derivatives and more.

A fast poisson image editing implementation that can utilize multi-core CPU or GPU to handle a high-resolution image input.

Distributed Keras Engine, Make Keras faster with only one line of code.

适用于高性能系统的多进程解压缩软件(A multiprocess decompression software for high-performance system)

Python Multi-Process Execution Pool: concurrent asynchronous execution pool with custom resource constraints (memory, timeouts, affinity, CPU cores and caching), load balancing and profiling capabilities of the external apps on NUMA architecture

Fit and compare complex models reliably and rapidly. Advanced nested sampling.