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BioDynaMo: an agent-based simulation platform for scalable computational biology research
arXiv - CS - Computational Engineering, Finance, and Science Pub Date : 2020-06-11 , DOI: arxiv-2006.06775
Lukas Breitwieser, Ahmad Hesam, Jean de Montigny, Vasileios Vavourakis, Alexandros Iosif, Jack Jennings, Marcus Kaiser, Marco Manca, Alberto Di Meglio, Zaid Al-Ars, Fons Rademakers, Onur Mutlu, Roman Bauer

Computer simulation is an indispensable tool for studying complex biological systems. In particular, agent-based modeling is an attractive method to describe biophysical dynamics. However, two barriers limit faster progress. First, simulators do not always take full advantage of parallel and heterogeneous hardware. Second, many agent-based simulators are written with a specific research problem in mind and lack a flexible software design. Consequently, researchers have to spend an unnecessarily long time implementing their simulation and have to compromise either on model resolution or system size. We present a novel simulation platform called BioDynaMo that alleviates both of these problems researchers face in computer simulation of complex biological systems. BioDynaMo features a general-purpose and high-performance simulation engine. The engine simulates cellular elements, their interactions within a 3D physical environment, and their cell-internal genetic dynamics. We demonstrate BioDynaMo's wide range of application with three example use cases: soma clustering, neural development, and tumor spheroid growth. We validate our results with experimental data, and evaluate the performance of the simulation engine. We compare BioDynaMo's performance with a state-of-the-art baseline, and analyze its scalability. We observe a speedup of 20--124$\times$ over the state-of-the-art baseline using one CPU core and a parallel speedup between 67$\times$ and 76$\times$ using 72 physical CPU cores with hyperthreading enabled. Combining these two results, we conclude that, on our test system, BioDynaMo is at least three orders of magnitude faster than the state-of-the-art serial baseline. These improvements make it feasible to simulate neural development with 1.24 billion agents on a single server with 1TB memory, and 12 million agents on a laptop with 16GB memory.

中文翻译:

BioDynaMo:用于可扩展计算生物学研究的基于代理的模拟平台

计算机模拟是研究复杂生物系统不可或缺的工具。特别是,基于代理的建模是描述生物物理动力学的一种有吸引力的方法。然而,有两个障碍限制了更快的进展。首先,模拟器并不总是充分利用并行和异构硬件。其次,许多基于代理的模拟器是针对特定的研究问题编写的,缺乏灵活的软件设计。因此,研究人员不得不花费不必要的长时间来实施他们的模拟,并且不得不在模型分辨率或系统大小上做出妥协。我们提出了一种称为 BioDynaMo 的新型模拟平台,它可以缓解研究人员在复杂生物系统的计算机模拟中面临的这两个问题。BioDynaMo 具有通用和高性能的模拟引擎。该引擎模拟细胞元素、它们在 3D 物理环境中的相互作用以及它们的细胞内部遗传动力学。我们通过三个示例用例展示了 BioDynaMo 的广泛应用:体细胞聚类、神经发育和肿瘤球体生长。我们用实验数据验证了我们的结果,并评估了仿真引擎的性能。我们将 BioDynaMo 的性能与最先进的基线进行比较,并分析其可扩展性。我们观察到在使用一个 CPU 内核的最先进基线上的加速比为 20--124$\times$,并且使用 72 个具有超线程的物理 CPU 内核的并行加速在 67$\times$ 和 76$\times$ 之间启用。结合这两个结果,我们得出结论,在我们的测试系统上,BioDynaMo 比最先进的串行基线至少快三个数量级。这些改进使得在具有 1TB 内存的单个服务器上使用 12.4 亿个代理以及在具有 16GB 内存的笔记本电脑上使用 1200 万个代理来模拟神经发育变得可行。
更新日期:2020-06-15
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