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Fractal Video Compression in OpenCL: An Evaluation of CPUs, GPUs, and FPGAs as Acceleration Platforms

Doris Chen, Deshanand Singh
Altera Toronto Technology Center, Toronto, Ontario, Canada
Altera whitepaper, 2013

@article{chen2013fractal,

   title={Fractal Video Compression in OpenCL: An Evaluation of CPUs, GPUs, and FPGAs as Acceleration Platforms},

   author={Chen, Doris and Singh, Deshanand},

   year={2013}

}

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Fractal compression is an efficient technique for image and video encoding that uses the concept of self-referential codes. Although offering compression quality that matches or exceeds traditional techniques with a simpler and faster decoding process, fractal techniques have not gained widespread acceptance due to the computationally intensive nature of its encoding algorithm. In this paper, we present a real-time implementation of a fractal compression algorithm in OpenCL [1]. We show how the algorithm can be efficiently implemented in OpenCL and optimized for multi-CPUs, GPUs, and FPGAs. We demonstrate that the core computation implemented on the FPGA through OpenCL is 3x faster than a high-end GPU and 114x faster than a multi-core CPU, with significant power advantages. We also compare to a hand coded FPGA implementation to showcase the effectiveness of an OpenCL-to-FPGA compilation tool.
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