Towards Blood Flow in the Virtual Human: Efficient Self-Coupling of HemeLB

J. W. S. McCullough, R. A. Richardson, A. Patronis, R. Halver, R. Marshall, M. Ruefenacht, B. J. N. Wylie, T. Odaker, M. Wiedemann, B. Lloyd, E. Neufeld, G. Sutmann, A. Skjellum, D. Kranzlmüller, and P. V. Coveney, Interface Focus, February 2021, Volume 11, 20190119, online 11 December 2020, doi:

Many scientific and medical researchers are working towards the creation of a virtual human—a personalized digital copy of an individual—that will assist in a patient’s diagnosis, treatment and recovery. The complex nature of living systems means that the development of this remains a major challenge. We describe progress in enabling the HemeLB lattice Boltzmann code to simulate 3D macroscopic blood flow on a full human scale. Significant developments in memory management and load balancing allow near linear scaling performance of the code on hundreds of thousands of computer cores. Integral to the construction of a virtual human, we also outline the implementation of a self-coupling strategy for HemeLB. This allows simultaneous simulation of arterial and venous vascular trees based on human-specific geometries.

The scientific and technical impact of the study can be summarized as:

  • HemeLB code is used to efficiently simulate blood flow in the entire human body
  • Simulations in the arterial and venous vascular trees of the Virtual Population model Yoon-sun demonstrate near linear scaling on hundreds of thousands of computer cores
  • A novel self-coupling strategy is used to communicate boundary conditions between different cores