Data Parallel Extensions for Python* Language
Enable standards-based accelerated computing on CPUs and GPUs without using low-level proprietary programming APIs. Optimize performance and portability by extending the familiar CPU programming model to a GPU with a compute follows data model.
Data Parallel Control Library (dpctl)
This library provides utilities for device selection, allocation of data on devices, tensor data structure, the Python* Array API Standard implementation, and support for the creation of user-defined data-parallel extensions.
Data Parallel Extension for NumPy*
This is a drop-in replacement for a subset of NumPy APIs that enable running on Intel CPU and GPUs.
Data Parallel Extension for Numba*
This extension enables you to program GPUs the same way CPUs are programmed with Numba.