Difference between revisions of "CoE Cluster April 2012"
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*[[/CUDA|Programmering med CUDA]] | *[[/CUDA|Programmering med CUDA]] | ||
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| − | Having investigated CUDA C programming for Nvidia graphics cards and the CUDA architecture, we made some performance measurements using a range of numbers of blocks and threads, executing in parallel. The test program calculated values of the [ | + | Having investigated CUDA C programming for Nvidia graphics cards and the CUDA architecture, we made some performance measurements using a range of numbers of blocks and threads, executing in parallel. The test program calculated values of the [http://en.wikipedia.org/wiki/Mandelbrot_set Mandelbrot Set ] on a pixel-by-pixel basis. |
*[http://mars.tekkom.dk/js/cuda_benchmark.htm CUDA Benchmark] (External JavaScript) | *[http://mars.tekkom.dk/js/cuda_benchmark.htm CUDA Benchmark] (External JavaScript) | ||
Revision as of 07:59, 1 May 2012
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Assignments
Results
Having investigated CUDA C programming for Nvidia graphics cards and the CUDA architecture, we made some performance measurements using a range of numbers of blocks and threads, executing in parallel. The test program calculated values of the Mandelbrot Set on a pixel-by-pixel basis.
- CUDA Benchmark (External JavaScript)
Mandelbrot Set drawn in 1,2 seconds, using a Master-Worker MPI pattern with 16 worker nodes and 1 master node (which collected calculated results from different parts of the image and output them to an X Window). Total image dimension 800 x 800 pixels.
Mandelbort Set drawn in 0,12 seconds, using a single NVidia CUDA capable graphics card (GeForce GTX 460) running 32 blocks and 128 threads in each block. Total image dimension 512 x 512 pixels.
[CUDA Benchmarking Results]
Slides
Litteratur Liste
- MPI
- Introduction to Parallel Computing
- CUDA Overview from Nvidia
- Nvidia CUDA C Programming Guide
- OpenCV Tutorial
- OpenCV Reference
- Skin Detection algorithms for use in OpenCV/CUDA trials