A highly scalable implementation of the lattice Boltzmann method demonstrated strong scaling for 3D high-resolution hemodynamic simulations on 1,572,864 cores, reducing time-to-solution.
A new highly scalable computational model significantly reduces time-to-solution for biofluidic simulations of the full arterial tree, potentially enabling per-patient risk stratification.
The potential impact of blood flow simulations on the diagnosis and treatment of patients suffering from vascular disease is tremendous. Empowering models of the full arterial tree can provide insight into diseases such as arterial hypertension and enables the study of the influence of local factors on global hemodynamics. We present a new, highly scalable implementation of the lattice Boltzmann method which addresses key challenges such as multiscale coupling, limited memory capacity and bandwidth, and robust load balancing in complex geometries. We demonstrate the strong scaling of a three-dimensional, high-resolution simulation of hemodynamics in the systemic arterial tree on 1,572,864 cores of Blue Gene/Q. Faster calculation of flow in full arterial networks enables unprecedented risk stratification on a perpatient basis. In pursuit of this goal, we have introduced computational advances that significantly reduce time-to-solution for biofluidic simulations.
Randles et al. (Tue,) conducted a other in Vascular disease. Highly scalable implementation of the lattice Boltzmann method was evaluated on Strong scaling of a three-dimensional, high-resolution simulation of hemodynamics. A highly scalable implementation of the lattice Boltzmann method demonstrated strong scaling for 3D high-resolution hemodynamic simulations on 1,572,864 cores, reducing time-to-solution.