numthreads

Set the number of threads used by OpenBLAS, MKL, OMP, NumExpr, and Accelerate

numthreads is a really tiny and simple Python package designed to set the number of threads for various computing libraries including OpenBLAS, Intel's Math Kernel Library (MKL), OpenMP, NumExpr, Accelerate, and Numba. The number of threads can be set via the command line or in Python code. The performance of many numerical algorithms varies significantly based on the number of threads employed. While increasing the number of threads can often accelerate these algorithms, it's not always the case. In some instances, using more threads may actually impede computational efficiency. Therefore, it's important to be able to easily set the number of threads used by these libraries.

• Simple and straightforward command-line interface.
• Sets thread count for OpenBLAS, MKL, OpenMP, NumExpr, and Accelerate.
• Context manager support for temporary thread setting in Python code.
• Cross-platform compatibility (Linux, macOS, Windows).
• Use as pytest plugin
• Tiny (≤7KB) and no dependencies.

📚 Table of Contents

• 📦 Installation
• 🚀 Quick Start
  • Using as a Python Module
  • Command Line Interface
    • Unix-like Systems (Linux, macOS, WSL)
    • Windows (PowerShell)
  • Get the number of threads
  • 🔌 Using as a pytest Plugin
• ❓ Getting Help

📦 Installation

To install numthreads, run the following command:

pip install numthreads

🚀 Quick Start

Get started with numthreads in a few seconds.

Using as a Python Module

You can also use numthreads as a Python module:

from numthreads import set_num_threads

set_num_threads(4)

This will set the number of threads using the following environment variables:

• OpenBLAS (via OPENBLAS_NUM_THREADS)
• MKL (via MKL_NUM_THREADS)
• OpenMP (via OMP_NUM_THREADS)
• NumExpr (via NUMEXPR_NUM_THREADS)
• Accelerate (via VECLIB_MAXIMUM_THREADS)
• Numba (via NUMBA_NUM_THREADS)

or use it as a context manager:

from numthreads import num_threads

with num_threads(4):
    # Your code here will run with the specified number of threads
    pass

To set OMP (OpenMP) threads at any time (OpenMP docs), you can use omp_set_num_threads or the omp_num_threads context manager:

from numthreads import omp_set_num_threads

omp_set_num_threads(4)

or

from numthreads import omp_num_threads

with omp_num_threads(4):
    # Your code here will run with the specified number of threads
    pass

Command Line Interface

After installing numthreads, you can easily set the number of threads used by supported libraries via the command line. For example, to print the command to set the number of threads to 4, run:

numthreads 4

Which will print the following:

export OPENBLAS_NUM_THREADS='4' ; export MKL_NUM_THREADS='4' ; export OMP_NUM_THREADS='4' ; export NUMEXPR_NUM_THREADS='4' ; export VECLIB_MAXIMUM_THREADS='4' ; export NUMBA_NUM_THREADS='4'

Unix-like Systems (Linux, macOS, WSL)

To apply the settings in your shell:

eval $(numthreads <number_of_threads>)

Windows (PowerShell)

In PowerShell, use:

Invoke-Expression $(numthreads <number_of_threads>)

Get the number of threads

To get the number of threads currently set, run:

eval $(numthreads 12)  # first set something
numthreads get

Which will print the following:

OPENBLAS_NUM_THREADS: 12
MKL_NUM_THREADS: 12
OMP_NUM_THREADS: 12
NUMEXPR_NUM_THREADS: 12
VECLIB_MAXIMUM_THREADS: 12
NUMBA_NUM_THREADS: 12

Check the numthreads -h message for more information:

usage: numthreads [-h] n

Set the number of threads for OpenBLAS, MKL, OMP, NumExpr, and Accelerate.
Usage: Run `numthreads <number>` to print the export commands. On Unix-like
systems (Linux, macOS, WSL), use `eval $(numthreads <number>)` in your shell
to apply these settings. On Windows, in PowerShell, use `Invoke-Expression
$(numthreads <number>)`.

positional arguments:
  n           Number of threads to set or use 'get' to display current
              settings.

options:
  -h, --help  show this help message and exit

🔌 Using as a pytest Plugin

numthreads can be used as a pytest plugin to automatically set the number of threads for your tests.

To use it, make sure numthreads is installed. Then, run pytest with the --numthreads option followed by the desired number of threads:

pytest --numthreads 1

This will set the number of threads for OpenBLAS, MKL, OMP, NumExpr, and Accelerate before running your tests.

❓ Getting Help

For more information, or to report issues, please visit numthreads GitHub repository.