A GPU accelerated study of aqueous humor dynamics in human eyes using the lattice Boltzmann method

Abstract

In this paper, we presented a 3D human eyes aqueous humor (AH) dynamics model, and additionally, designed and optimized it using GPU technology. First, the feasibility of the model is demonstrated through validation. Then, the effect of different factors on AH flow was investigated using the validated model. The experimental results showed that AH flow more rapidly when standing than supine; the intraocular temperature has the greatest effect on AH flow compared to other factors; the AH secretion rate and trabecular meshwork (TM) permeability had a greater effect on intraocular pressure (IOP). Corneal indentation and ovoid anterior chamber (AC) can also affect AH flow. Finally, the PartSparse algorithm based GPU can save more than 50% of the memory consumption and achieves a performance of 1491.29 MLUPS and a Speedup of 837.61 times.

Keywords

• lattice boltzmann method
• aqueous humor dynamics
• gpu
• sparse matrix