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FPGA-GPU-CPU Heterogenous Architecture for Real-time Cardiac Physiological Optical Mapping

Pingfan Meng, Matthew Jacobsen, Ryan Kastner
Department of Computer Science and Engineering, University of California, San Diego, 9500 Gilman Dr. La Jolla, CA 92093, USA
International Conference on Field-Programmable Technology, 2012
@article{meng2012fpga,

   title={FPGA-GPU-CPU Heterogenous Architecture for Real-time Cardiac Physiological Optical Mapping},

   author={Meng, P. and Jacobsen, M. and Kastner, R.},

   year={2012}

}

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Real-time optical mapping technology is a technique that can be used in cardiac disease study and treatment technology development to obtain accurate and comprehensive electrical activity over the entire heart. It provides a dense spatial electrophysiology. Each pixel essentially plays the role of a probe on that location of the heart. However, the high throughput nature of the computation causes significant challenges in implementing a real-time optical mapping algorithm. This is exacerbated by high frame rate video for many medical applications (order of 1000 fps). Accelerating optical mapping technologies using multiple CPU cores yields modest improvements, but still only performs at 3:66 frames per second (fps). A highly tuned GPU implementation achieves 578 fps. A FPGA-only implementation is infeasible due to the resource requirements for processing intermediate data arrays generated by the algorithm. We present a FPGAGPU-CPU architecture that is a real-time implementation of the optical mapping algorithm running at 1024 fps. This represents a 273x speed up over a multi-core CPU implementation.
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