12544

Multi-Core Programming Design Patterns: Stream Processing Algorithms for Dynamic Scene Perceptions

Kannappan Palaniappan
University of Missouri, 316 University Hall, Columbia, MO 65211-3020
University of Missouri, 2014

@techreport{palaniappan2014multi,

   title={Multi-Core Programming Design Patterns: Stream Processing Algorithms for Dynamic Scene Perceptions},

   author={Palaniappan, Kannappan},

   year={2014},

   institution={DTIC Document}

}

Download Download (PDF)   View View   Source Source   

1688

views

We have implemented, tested, validated and benchmarked a scalable parallel implementations of the integral histogram algorithm critical for computer vision tasks for fast multiscale subwindow-based object searching, motion analysis and content-based image retrieval applications. Several integral histogram kernels using CUDA optimizations for many core GPUs were investigated. The integral histogram algorithm was also parallelized using the StarSs programming model in collaboration the Barcelona Supercomputing Center for several architectures including Cell/B.E., GPU and SMP. The Cell/B.E. implementation of the integral histogram using cross-weave scan and 16 bins for a 640×480 image reaches 160 fr/sec using 8 SPEs. The wavefront scan for the same sized image reaches almost 200 fr/sec but critically depends on the block size. The GPU implementation of the integral histogram was 60 times faster than the sequential CPU version for a 1K x 1K image reaching 49 fr/sec and 21 times faster for 512 x 512 images reaching 194 fr/sec. The implemented code has been delivered to AFRL for transition to other programs like CETE.
No votes yet.
Please wait...

* * *

* * *

HGPU group © 2010-2024 hgpu.org

All rights belong to the respective authors

Contact us: