Intel® IPP 2017 Beta is now available. The release provides broad and release quality optimizations for AVX512 and AVX2 (KNL and SKL). This results in higher performance and more efficient data management across a wide range of applications like image and single processing, computer vision, and data compression. This release also support the Super-resolution (huge image) through new wrappers that support 64-bit data length (Intel® IPP 64x functions) and the new integration wrappers which provide easy-to-use APIs for the Intel IPP functionality:
Intel IPP 2017 beta release is available as a part of the Intel Parallel Studio XE 2017 Beta, and will be available at Intel System Studio 2017 Beta soon.
To sign up for the Intel Parallel Studio XE 2016 Beta, please use the following link:
Registration Link: Click the link here for Registration
What’s New in Intel® IPP 2017 Beta:
- Added new APIs (Intel® IPP 64x functions) to support 64-bit data length in the image and signal processing domains:
- Added integration wrappers for some image processing and computer vision functions. The wrappers provide the easy-to-use C and C++ APIs for Intel® IPP functions, and they are available as a separate download soon..
- Extended optimization for Intel® AVX-512, Intel® AVX2, Intel® SSE4.2 instruction set on Intel® MIC Architectures, Intel® Xeon® , Intel® Core™, and Intel® Atom™ processors.
- Signal Processing:
- Added the ippsIIRIIR functions that perform zero-phase digital IIR filtering.
- Added 64-bit data length support to the ippsSortRadixAscend functions.
- Image Processing:
- Added the ippiScaleC functions to support image data scaling and shifting for different data types.
- Data Compression:
- Added the patch files for the zlib compression and decompression functions. The patches provide drop-in optimization with Intel® IPP functions, and support zlib version 1.2.5.3, 1.2.6.1, 1.2.7.3 and 1.2.8.
- Removed the tutorial from the installation package, and its sample code and documentation are now provided online (https://software.intel.com/en-us/product-code-samples).
Please find more information on Intel IPP 2017 Beta release note
Your feedback and question is welcome during your evaluation.