Useful links

Companion documentation

Document	Description
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
SYCL*	Standard for writing C++-like codes for heterogeneous computing
DPC++	Free e-book on how to program data-parallel devices using Data Parallel C++
OpenCl*	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
Numpy*	Documentation for Numpy - foundational CPU library for array programming. Used in conjunction with Data Parallel Extension for Numpy*.
Numba*	Documentation for Numba - Just-In-Time compiler for Numpy-like codes. Used in conjunction with Data Parallel Extension for Numba*.

To-Do

Todo

Document debugging section

original entry