GPU accelerated simulation of the human arterial circulation

A GPU accelerated implementation of a reduced-order model of the human arterial circulation is introduced. The computationally intensive tasks of the algorithm (namely, the computation of the flow rate and area values at the interior grid points of the domain) have been migrated to the GPU. The CPU not only coordinates the actions performed by the GPU, but it also computes the inflow, bifurcation and outflow points. The GPU operations have been included in a single kernel, which has been optimized towards high computational intensity and low global memory throughput in order to obtain good results even for small arterial trees. Although the amount of data to be transferred between CPU and GPU is small, its scattered nature has lead to an approach where the entire arrays are copied back and forth. The speed-up obtained for the code migrated from the host to the device is of around 30×, while the speed-up of the entire application is of 4.5-4.7×. An important property of the proposed approach is that the speed-up obtained remains constant for arterial trees which are up to ten times smaller than e regular tree representing the large arteries of the human cardiovascular system. Hence it can be used with the same impact for simulations of entire systemic trees and of smaller localized trees.