Sunday, 30 September 2012

Multicore Processors and Image Processing - I

         Quad-core based desktops and laptops have become order of the day. These multi-core processors after long years of academic captivity have come to the limelight. Study of multi-core and multi-processors, come under the field of High Performance Computing.
          Two or more processors are fabricated in a single package then it is called multi-core processor. Multi-processors and multi-process (single processor but multiple application are running simultaneously) are different from multi-core processors. Quad (four) and Duo (two) are commonly used multi-core processor by general public. With prevailing fabrication technology, race to increase raw clock power beyond 3GHz is nearing the end.  Further increase in computing power, is possible with deploying Parallel computing concept.  This is the reason why, all the manufacturers are introducing multi-core processors.

           Image processing algorithms are exhibits high degree parallelism.  Most of algorithms have loop(s) and they iterate through a pixel, row or an image region.  Let us take an example loop, which has to iterate 200 times.  Single processor will iterate 200 times and in a quad-core each processor will iterate 50 times only. Obviously quad-core will finish the task much faster than single processor. To achieve the stated speed, programs have to be slightly modified and multi-core optimized compilers are required.

Image size         Time to execute in (ms)
        (Single-core)   (Multi-core)
256x256                   18                          8
512x512                   65                        21
1024x1024             260                        75

       Amount of time needed to twist  Lenna image is given in the above table. Lenna image with 1024x 1024 takes 260ms in single core and 75ms in multi-core to perform twist operation. From this it is very clear, in a single-core processor, as image size increases execution time increases exponentially but in multi-core processor in goes in linear fashion [1].

        Algorithms will exhibit either fine grain or medium grain or course grain parallelism. Smoothing, sharpening, filtering and convolution image processing functions operate on entire image and they are classified as fine-grain systems.  Medium grain parallelism is exhibited by Hough transform, motion analysis and the functions operate on part of an image.  Position estimation and object recognition comes under the class of course grain and parallelism exhibited is very less [2].  Algorithms can be split into memory-bound and CPU bound algorithms. In CPU bound algorithms no of cores helps to achieve linear-speed up subject to Amdahl's law [3].

       Multiprocessors are developed by Intel and AMD are very popular. Following table content got from [3].
Multicore Processor        No of core    Clock speed
Intel Xeon E5649                    12                2.53GHz
AMD Opteron 6220               16                3.00GHz
AMD Phenom X4(9550)          4                2.20GHz

        Intel Xeon was launched in 2002.  Intel introduced simultaneous multiple threading capability and named it as Hyper Threading. It has also launched Core 2 Duo T7250, which is a low voltage mobile processor runs at 2GHz. Sony’s Playstation 3 has a very powerful multi-core processor.  This is called Cell Broadband Engine and it is developed jointly by Sony, Toshiba and IBM.  It has a 64bit PowerPC processor connected by a circular bus to eight RISC (Reduced Instruction Set Computing) with 128 SIMD (Single Instruction Multiple Data) architecture based co-processors. SIMD is well suited  to exploit  fine grain parallelism.

In the part two series GPU and OpenMP Application Program Interface (API) wil l be discussed.


[1] Greg Slabaugh, Richard Boyes, Xiaoyun Yang, "Multicore Image Processing with OpenMP", Appeared in IEEE Signal Processing Magazine, March 2010, pp134-138. But it can be downloaded from (PDF, 1160KB )
[2] Trupti Patil, "Evaluation of Multi-core Architecture for Image Processing,"  MS Thesis,  year 2009, at Graduate School of Clemson University (PDF, 1156KB)

[3] OpenMP in GraphicsMagick,

  • Please read [1], as it is insightful and language used is simpler compared to standard technical articles.
  • Warped Lena and above table was adapted from [1] and not copied.  GIMP software was used to create the warped effect on the Lenna image.