MATLAB Answers

Dehuan Xin

Performance Issue of 'imrotate' in double precision mode

Asked by Dehuan Xin
on 26 Mar 2013


Recently I use 'imrotate' a lot, and I see a 25 times speed boost with single-precision data compared with double-precision.

I am quite astonished because I thought single-precision were usually 'only' twice as fast as double-precision.

I ran this code on Intel Core Duo E8400 @ 3Ghz, with Matlab 2012A 64 bit. Double precision takes 10.461 seconds, while single precision takes 0.456s.

for i=1:1:180

In profiler, I saw that "imrotatemex(MEX-file)" was called if input is single-precision but was not used if input is double-precision, which makes a huge difference in speed.

Is it possible that Mathworks update 'imrotate' so that "imrotatemex(MEX-file)" works with both single and double-precision data?



Dehuan Xin


3 Answers

Answer by Teja Muppirala
on 26 Mar 2013

Hi Dehuan,

If you are able to upgrade to a newer version, performance improvements for IMROTATE were implemented in R2012b. Moreover, R2013a adds GPU support for IMROTATE. See the release notes for more information.


Hi, Teja

Does the data-type optimization (UINT8, UINT16, SINGLE) also apply to GPU-computing?

As of R2013a, IMROTATE on the GPU supports UINT8, UINT16, LOGICAL, and SINGLE inputs. It does not support DOUBLE inputs.

Answer by Alex Taylor
on 26 Mar 2013

Hi Dehuan,

As Teja pointed out, IMROTATE was hardware optimized for double-precision inputs in R2012b. If you are able to update to a newer version, you will see a dramatic increase in performance for double inputs in IMROTATE.


Answer by Yair Altman
on 30 Mar 2013
Edited by Yair Altman
on 30 Mar 2013

This is a limitation imposed by MathWorks in imrotate.m (subfunction useIPP), purportedly because Intel's Performance Primitives Library (IPPL) does not support double precision (although it does). Modifying useIPP() to accept doubles will not help since imrotatemex itself rejects this data type...

The big performance boost in R2012b appears to result from simply removing this limitation in both useIPP and imrotatemex.


Join the 15-year community celebration.

Play games and win prizes!

Learn more
Discover MakerZone

MATLAB and Simulink resources for Arduino, LEGO, and Raspberry Pi

Learn more

Discover what MATLAB® can do for your career.

Opportunities for recent engineering grads.

Apply Today

MATLAB Academy

New to MATLAB?

Learn MATLAB today!