Intel® Distribution for Python*

High-Performance Python

• Take advantage of the most popular and fastest growing programming language with underlying instruction sets optimized for Intel® architectures.
• Achieve highly efficient multithreading, vectorization, and memory management, and scale scientific computations efficiently across a cluster.
• Core packages include Numba, NumPy, SciPy, and more.

Accelerated Performance with Minimal or No Code Changes

• Achieve near-native performance through acceleration of core Python numerical and scientific packages that are built using Intel® Performance Libraries.
• Compile your custom code using core compiler technologies such as Numba* and Cython. These apply vectorization and multithreading to your code, bringing Python to new levels.
• Leverage composable parallelism through Intel® oneAPI Threading Building Blocks (oneTBB) and symmetric multiprocessing (SMP). These technologies help you avoid excess headroom, use nested parallelism without oversubscription, and optimize particular workloads for the highest performance.
• Program for multiple devices using the same programming model, DPPy (Data Parallel Python), without rewriting CPU code to device code. Its included package, dpCtl, lets you control execution and data management across the host and devices.
• Run your workloads on data-parallel and heterogeneous hardware without having to go out of the Python ecosystem, while simultaneously not compromising on performance using DPPy.

Operating systems:

• Linux*
• Windows® 10
• macOS*

Language:

• Python 3.7.4

Package management:

• conda*
• PIP*

Compatible with:

• Microsoft Visual Studio*
• PyCharm*

For more information, see the system requirements.