Skip to main content

NumPy optimized with Intel(R) MKL library

Project description

Optimized implementation of numpy, leveraging Intel® Math Kernel Library to achieve highly efficient multi-threading, vectorization, and memory management. Accelerates numpy's linear algebra, Fourier transform, and random number generation capabilities, as well as select universal functions. Drop-in replacement that maintains Python and C API compatibility with numpy. Additional details can be found in our SciPy 2017 conference proceedings.

One of many Intel® accelerated Python packages and performance library runtimes available on PyPI, and as part of Intel® Distribution for Python.

For latest release updates and security notifications, please subscribe to the Intel® Distribution for Python Community forum.

Free to use and redistribute pursuant to the Intel Simplified Software License.

Project details


Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page