High Performance Computing
High performance computing (HPC) is the foundation of our research. We develop new computational methods that allow complex biological systems to be simulated at unprecedented scale, transforming problems that once required days or weeks into clinically relevant workflows.
At the center of this effort is HARVEY, our massively parallel computational fluid dynamics platform for patient specific blood flow simulation. HARVEY is designed to model blood flow throughout the vascular system with high accuracy while scaling efficiently across the world's fastest supercomputers. These capabilities enable us to study disease mechanisms, evaluate treatment strategies, and build personalized vascular digital twins that support clinical decision making.
Our research addresses fundamental challenges in scientific computing, including multiscale simulation, GPU computing, performance portability, adaptive algorithms, load balancing, and scalable data analysis. We develop algorithms that make better use of modern heterogeneous computing architectures while reducing memory requirements and improving computational efficiency.
HARVEY has scaled efficiently across multiple generations of leadership class supercomputers, from IBM Blue Gene/Q to today's GPU accelerated exascale systems, including Frontier at Oak Ridge National Laboratory and Aurora at Argonne National Laboratory. Along the way, our work has contributed to major advances in large scale cardiovascular simulation, including recognition as an ACM Gordon Bell Prize Finalist.
As simulations continue to grow in size and complexity, we are integrating AI, in situ data analysis, and interactive visualization directly into the simulation workflow. These advances reduce data movement, accelerate scientific discovery, and bring us closer to real time, patient specific cardiovascular modeling.