Integrated Performance Primitives

Last updated
Intel Integrated Performance Primitives
Developer(s) Intel
Stable release
2021.11.0 / March 28, 2024;5 months ago (2024-03-28) [1] [2]
Written in C/C++
Operating system Linux, macOS, Microsoft Windows
Type Library or framework
License Proprietary, freeware [3]
Website software.intel.com/intel-ipp   OOjs UI icon edit-ltr-progressive.svg

Intel Integrated Performance Primitives (Intel IPP) is an extensive library of ready-to-use, domain-specific functions that are highly optimized for diverse Intel architectures. Its royalty-free APIs help developers take advantage of single instruction, multiple data (SIMD) instructions. [4]

Contents

The library supports Intel and compatible processors and is available for Linux, macOS and Windows. It is available separately or as a part of Intel oneAPI Base Toolkit. [4]

Intel IPP releases use a semantic versioning schema, so that even though the major version looks like a year (YYYY), it is not technically meant to be a year. So it might not change every calendar year. [5]

Features

The library takes advantage of processor features including MMX, SSE, SSE2, SSE3, SSSE3, SSE4, AVX, AVX2, AVX-512, AES-NI and multi-core processors. [6] Intel IPP includes functions for:

Organization

Intel IPP is divided into four major processing groups: signal processing (with linear array or vector data), image processing (with 2D arrays for typical color spaces), data compression, and cryptography. [6]

Half the entry points are of the matrix type, a third are of the signal type, and the remainder are of the image and cryptography types. Intel IPP functions are divided into 4 data types: data types include 8u (8-bit unsigned), 8s (8-bit signed), 16s, 32f (32-bit floating-point), 64f, etc. Typically, an application developer works with only one dominant data type for most processing functions, converting between input to processing to output formats at the end points. [6]

History

Counterparts

See also

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References

  1. 1 2 3 4 5 6 7 "Intel® Integrated Performance Primitives Library Release Notes and New Features". software.intel.com.
  2. 1 2 3 4 "Intel® IPP 2020 Bug Fixes". software.intel.com.
  3. "No Cost Options for Intel Parallel Studio XE, Support yourself, Royalty-Free".
  4. 1 2 "Intel® Integrated Performance Primitives". Intel. Retrieved 2024-04-03.
  5. "Intel® oneAPI Toolkit and Component Versioning Schema". Intel. Retrieved 2024-04-03.
  6. 1 2 3 "Intel Integrated Performance Primitives (Intel IPP) Library".
  7. "Intel Integrated Performance Primitives (Intel IPP) Library 6.1 Release Notes".
  8. "Intel Integrated Performance Primitives (Intel IPP) Library 7.1 Release Notes".
  9. "Intel Integrated Performance Primitives (Intel IPP) Library 8.0 Release Notes".
  10. "Intel Integrated Performance Primitives (Intel IPP) Library 8.1 Release Notes".
  11. "Intel Integrated Performance Primitives (Intel IPP) Library 8.2 Release Notes".
  12. "Intel Integrated Performance Primitives (Intel IPP) Library 9.0 Release Notes".
  13. "Intel Integrated Performance Primitives (Intel IPP) Library 9.0 Github".
  14. 1 2 3 4 5 6 7 Harrison, Pamela. "Intel® Integrated Performance Primitives Release Notes for Intel®..." Intel. Retrieved 2024-04-03.
  15. Harrison, Pamela. "Intel® Integrated Performance Primitives Release Notes for Intel®..." Intel. Retrieved 2024-07-23.
  16. "NVIDIA Performance Primitives (NPP)". NVIDIA Developer. Retrieved 2024-04-03.