OpenACC Acceleration of an Agent-Based Biological Simulation Framework

TL;DR

This paper demonstrates how OpenACC can significantly accelerate agent-based biological simulations, especially diffusion processes, enabling longer and more detailed cancer modeling on diverse hardware platforms.

Contribution

The paper introduces the use of OpenACC to accelerate biological diffusion operators in PhysiCell, achieving high speedups on GPU and multicore CPU systems with a unified code base.

Findings

40x speedup on NVIDIA A100 GPU

9x speedup on AMD EPYC CPU

Single source code for CPU and GPU acceleration

Abstract

Computational biology has increasingly turned to agent-based modeling to explore complex biological systems. Biological diffusion (diffusion, decay, secretion, and uptake) is a key driver of biological tissues. GPU computing can vastly accelerate the diffusion and decay operators in the partial differential equations used to represent biological transport in an agent-based biological modeling system. In this paper, we utilize OpenACC to accelerate the diffusion portion of PhysiCell, a cross-platform agent-based biosimulation framework. We demonstrate an almost 40x speedup on the state-of-the-art NVIDIA A100 GPU compared to a serial run on AMD's EPYC 7742. We also demonstrate 9x speedup on the 64 core AMD EPYC 7742 multicore platform. By using OpenACC for both the CPUs and the GPUs, we maintain a single source code base, thus creating a portable yet performant solution. With the simulator's most significant computational bottleneck significantly reduced, we can continue cancer simulations over much longer times.