Scalable, High Performance Fourier Domain Optical Coherence Tomography: Why FPGAs and Not GPGPUs

Jian Li, Marinko V. Sarunic, Lesley Shannon
School of Engineering Science, Simon Fraser University, Burnaby BC, Canada
Proceedings of the 2011 IEEE 19th Annual International Symposium on Field-Programmable Custom Computing Machines, FCCM ’11, 2011


   title={Scalable, High Performance Fourier Domain Optical Coherence Tomography: Why FPGAs and Not GPGPUs},

   author={Li, J. and Sarunic, M.V. and Shannon, L.},

   booktitle={Field-Programmable Custom Computing Machines (FCCM), 2011 IEEE 19th Annual International Symposium on},





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Fourier Domain Optical Coherence Tomography (FD-OCT) is an emerging biomedical imaging technology featuring ultra-high resolution and fast imaging speed. Due to the complexity of the FD-OCT algorithm, real time FD-OCT imaging demands high performance computing platforms. However, the scaling of real-time FD-OCT processing for increasing data acquisition rates and 3-dimensional (3D) imaging is quickly outpacing the performance of general purpose processors. Our research analyzes the scalability of accelerating FD-OCT processing on two potential implementation platforms: General Purpose Graphical Processing Units (GPGPUs) and Field Programmable Gate Arrays (FPGAs). We implemented a complete FD-OCT system using a NVIDIA GPGPU as co-processor, with a speed up of 6.9x over general purpose processors (GPPs). We also created a hardware processing engine using FPGAs with a speed up of 15.5x over GPPs for a single pipeline, which can be replicated to further increase performance. Our analysis of the performance and scalability for both platforms shows that, while GPGPUs offer an easy and low cost solution for accelerating FD-OCT, FPGAs are more likely to match the long term demands for real-time, 3D, FD-OCT imaging.
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