Comments on: Multithreaded FFT functions in MATLAB R2009a

By: Steve

Steve — Mon, 13 Jul 2009 13:03:43 +0000

Khairiah—The MATLAB FFT functions work in floating point. You can convert your 16-bit unsigned integer data to floating point (single or double), compute the FFT, and then convert back.

By: khairiah

khairiah — Fri, 10 Jul 2009 06:11:01 +0000

Hi Steve,

Based on documentation,fft supports inputs of data types double and single .Is fft also support data type sign and unsigned integer for 8bit and 16bit image?
I have problems,where i need to input 16bit unsigned data into fft function,so that I can get the same unsigned 16 bit output.

By: Steve

Steve — Wed, 29 Apr 2009 12:43:18 +0000

Erik—We are always looking at technology options, but I can’t be specific about our plans.

You are correct that imfilter and convn do not use frequency-domain-based implementations.

imfilter does use the Intel IPP library for some inputs, and IPP exploits the extended instruction sets you mentioned. IPP does not support 3-D filtering, however.

By: erik

erik — Wed, 29 Apr 2009 01:20:50 +0000

hi steve-
are you considering using CUDA? i believe the speedup would be substantial. i would like to make a pixel shader to do n-d filtering on the GPU. i need 3-dimensional (inseparable, circular) filtering in real time for psychophysical/neurophysiology experiments, using psychtoolbox, which provides an interface btw matlab and the GPU, including shaders. there is a 2-d filtering example provided, and i’m trying generalize it by translating the implementation in imfilter_mex.h/ndim_filter() (or \toolbox\matlab\datafun\convnc.cpp\convolve()) for use as a shader.

the rough size of my problem is to show ~ 50×50 movie at 100hz, filtered by a ~ 35×35x12 kernel (tho even bigger would be even better). using imfilter this takes ~8x real time on a 2.6GHz core2 duo, and i didn’t see any speedup from upgrading to 2009a, i think because fft is not used by either imfilter or convn.

i’m finding all the index bookkeeping to be a headache. i was wondering if this would be an easy problem for you to demo, and a great excuse for exploring if using the GPU in matlab (esp. image/signal processing) could be an important market opportunity for mathworks (as has been demonstrated by folding@home, which saw a speed up of several orders of magnitude, for example). a less preferable alternative would be to use the FPU — neither example seems to make use of vectorized SIMD calls that have long been available — why is that?

By: Steve

Steve — Mon, 20 Apr 2009 13:20:50 +0000

Jason—No, the FFT implementation is not limited to two cores. However, other factors in the computation can limit the speedup achieved. For example, cache misses when computing the one-dimensional FFT along the non-unit-stride dimension can dominate overall execution time.

By: Jason Merrill

Jason Merrill — Sat, 18 Apr 2009 20:46:10 +0000

This is great news. Thanks for your work.

Is the parallelism limited to only two cores at this point? I was excited by the 2x speedup for a 1024×1024 fft2 on my dual core laptop, but a little surprised that the speedup was still only 2x on our 8 core machine.