Intel® Distribution for Python* Documentation
Documentation & Code Samples
Documentation
- Get Started
- Release Notes
- Known Issues
- End User License Agreement (EULA)
- Data Parallel Extensions for Python*
- Data Parallel Extension for NumPy*
- Data Parallel Extension for Numba*: Documentation | Get Started Guide
- Data Parallel Control (dpctl): Documentation | Get Started
Code Samples
- Examples of Data Parallel Extension for Python
Use these Hello World examples to get started with Data Parallel Extensions for Python. - Intel Distribution for Python: NumPy vs Data Parallel Extension for Numba (numba-dpex)
Learn how to use and optimize a k-nearest neighbor (KNN) model by numba-dpex operations without sacrificing accuracy. Run the KNN algorithm using three different libraries: NumPy, Numba, and numba-dpex. - Pairwise Distance: Open Source XPU Programming with Data Parallel Extension for Python*
Learn how Data Parallel Extension for NumPy and Data Parallel Extension for Numba can be used to compute pairwise distance in NumPy code efficiently and scale performance through open source heterogeneous computing and DPC++ (the oneAPI implmentation of SYCL*) compilation.
Training
Get Started
- What is Intel Distribution for Python? An Introduction
- A Guide to Multithreading in Python
- How to Create a Deep Learning Environment for Computer Vision
Data Parallel Extensions for Python
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