128.heartwall
SPEC ACCEL Benchmark Description File

Benchmark Name

128.heartwall


Benchmark Author

University of Virginia


Benchmark Program General Category

Structured Grid, Medical Imaging


Benchmark Description

The Heart Wall application tracks the movement of a mouse heart over a sequence of 104 609x590 ultrasound images to record response to the stimulus. In its initial stage, the program performs image processing operations on the first image to detect initial, partial shapes of inner and outer heart walls. These operations include: edge detection, SRAD despeckling (also part of Rodinia suite) [2], morphological transformation and dilation. In order to reconstruct approximated full shapes of heart walls, the program generates ellipses that are superimposed over the image and sampled to mark points on the heart walls (Hough Search). In its final stage (Heart Wall Tracking presented here) [1], program tracks movement of surfaces by detecting the movement of image areas under sample points as the shapes of the heart walls change throughout the sequence of images.


Input Description

The input sequence of images is presented in the file test.avi. The number of frames to process is passed in on the command line. The starting endo and epi points are presented in the file input.txt.


Output Description

The benchmark records summary information for each frame of the number of frames requested (endo, epi).

The output file heartwall.out contains detailed timing information about the run. It also shows which device was selected along with what devices where available to OpenCL.


Programming Language

C


Known portability issues

None


Reference

https://www.cs.virginia.edu/~skadron/wiki/rodinia/index.php/Main_Page

[1] L. G. Szafaryn, K. Skadron, and J. J. Saucerman. "Experiences Accelerating MATLAB Systems Biology Applications." In Proceedings of the Workshop on Biomedicine in Computing: Systems, Architectures, and Circuits (BiC) 2009, in conjunction with the 36th IEEE/ACM International Symposium on Computer Architecture (ISCA), June 2009.

[2] Y. Yu, S. Acton, Speckle reducing anisotropic diffusion, IEEE Transactions on Image Processing 11(11)(2002) 1260-1270.


Last Updated: February 3, 2014