High performance computing for Optical Diffraction Tomography

This paper analyses several parallel approaches for the development of a physical model of Non-linear ODT for its application in velocimetry techniques. The main benefits of its application in HPIV are the high accuracy with non-damaging radiation and its imaging capability to recover information from the vessel wall of the flow. Thus ODT-HPIV is suitable for microfluidic devices and biofluidic applications. Our physical model is based on an iterative method which uses double-precision complex numbers, therefore it has a high computational cost. As a result, High Performance Computing is necessary for both: implementation and validation of the model. Concretely, the model has been parallelized by means of different architectures: shared-memory multiprocessors and graphics processing units (GPU) using the CUDA device.