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 Intel System Studio 2017 Beta.
To sign up for the Intel Parallel Studio XE 2017 Beta:
Please visit the Intel Parallel Studio Beta Registration Page
To sign up for the Intel System Studio 2017 Beta:
Please visit the Intel System Studio Beta Page
What’s New in Intel® IPP 2017 Beta:
Please find more information on Intel IPP 2017 Beta release note
Your feedback and question is welcome during your evaluation.
Adriaan and Royi,
Thanks for the feedback. The threaded can be installed as an optionally package. Check this page for a few detail:
Since major of IPP functions are the low level primitives, threading at high level is more effective, For the 2D FFT, have you got chance to check our external thread example? They are located at: ipp\examples\ipp_examples_win.zip\examples\ipp_thread
Thanks for the feedback. I am tracking the request to add the threaded FFT functions in IPP high level wrappers code. For the FFT, are you using the 2D FFT function, or 1D? What is the transform type?
Also besides the FFT functions, are you want any other functions for the high level threading?
For image processing, I use the 2D real-to-packed-complex forward and packed-complex-to-real inverse FFT transforms extensively, both in-place and out-of-place. I quite prefer complex-interleaved over complex-split. incidentally, I use 1D signal FFT forward and inverse FFT transforms, for calculating reponse curves of filters (not speed critical). But I also write audio software and plan to use 1D FFTs for them in the future (and then they will be time-critical).
Any IPP function that can not be easily tiled, requires internal threading, like
• Fast Fourier Transform
• Discrete Cosine Transform
• Wavelet Transforms
As a sidebar, I note that of the many IPP functions I tried, most were quite fast, with the exception of
• 32-bit median (see my message on the issue)
• bilateral filter
Adriaan van Os