OpenACC Acceleration of an Agent-Based Biological Simulation Framework

被引:2
|
作者
Stack, Matt [1 ]
Macklin, Paul [2 ]
Searles, Robert C. [1 ]
Chandrasekaran, Sunita [3 ]
机构
[1] NVIDIA Corp, Santa Clara, CA 95051 USA
[2] Indiana Univ, Dept Intelligent Syst Engn, Bloomington, IN 47408 USA
[3] Univ Delaware, Dept Comp & Informat Sci, Newark, DE 19716 USA
基金
美国国家科学基金会;
关键词
Codes; Biological system modeling; Computational modeling; Accelerated aging; Memory management; Graphics processing units; Numerical models;
D O I
10.1109/MCSE.2022.3226602
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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 article, 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-ofthe-art NVIDIA Ampere 100 GPU compared to a serial run on AMD's EPYC7742. We also demonstrate 9x speedup on the 64-core AMD EPYC 7742 multicore platform. By using OpenACCfor both the CPUs and the GPUs, wemaintain a single source code base, thus creating a portable yet performant solution. With the simulator'smost significant computational bottleneck significantly reduced, we can continue cancer simulations over much longer times.
引用
收藏
页码:53 / 63
页数:11
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