Useful links

Companion documentation



Data Parallel Extension for Numpy*

Documentation for programming NumPy-like codes on data-parallel devices

Data Parallel Extension for Numba*

Documentation for programming Numba codes on data-parallel devices as you program Numba on CPU

Data Parallel Control

Documentation how to manage data and devices, how to interchange data between different tensor implementations, and how to write data parallel extensions

Intel VTune Profiler

Performance profiler supporting analysis of bottlenecks from function leve down to low level instructions. Supports Python and Numba

Intel Advisor

Analyzes native and Python codes and provides the advice for better composition of heterogeneous algorithms

Python* Array API Standard

Standard for writing portable Numpy-like codes targeting different hardware vendors and frameworks operating with tensor data


Standard for writing C++-like codes for heterogeneous computing


Free e-book on how to program data-parallel devices using Data Parallel C++


OpenCl* Standard for heterogeneous programming

IEEE 754-2019 Standard for Floating-Point Arithmetic

Standard for floating-point arithmetic, essential for writing robust numerical codes

David Goldberg, What every computer scientist should know about floating-point arithmetic

Scientific paper. Important for understanding how to write robust numerical code


Documentation for Numpy - foundational CPU library for array programming. Used in conjunction with Data Parallel Extension for Numpy*.


Documentation for Numba - Just-In-Time compiler for Numpy-like codes. Used in conjunction with Data Parallel Extension for Numba*.



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