Performance Issue of 'imrotate' in double precision mode

2 次查看（过去 30 天）
Dehuan Xin
Dehuan Xin 2013-3-26
Hi
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.
s=randn(400,400);
for i=1:1:180
imrotate(s,i);
end
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?
Thanks
Best
Dehuan Xin

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回答（3 个）

Teja Muppirala
Teja Muppirala 2013-3-26
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.
http://www.mathworks.com/help/images/release-notes.html
  2 个评论
Dehuan Xin
Dehuan Xin 2013-3-26
Hi, Teja
Does the data-type optimization (UINT8, UINT16, SINGLE) also apply to GPU-computing?
Teja Muppirala
Teja Muppirala 2013-3-26
As of R2013a, IMROTATE on the GPU supports UINT8, UINT16, LOGICAL, and SINGLE inputs. It does not support DOUBLE inputs.

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Alex Taylor
Alex Taylor 2013-3-26
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.
Yair Altman
Yair Altman 2013-3-30
编辑：Yair Altman 2013-3-30
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.

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