GPU computing for systems biology
GPU computing for systems biology
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DOI：
10.1093/bib/bbq006
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发表时间：
2010-05-01
影响因子：
9.5
通讯作者：
Prandi, Davide
中科院分区：
文献类型：
--
作者：
Dematte, Lorenzo;Prandi, Davide
开发复杂生物系统的详细、连贯的模型被认为是整合越来越多的实验数据的关键要求。此外，生物化学模型的计算机模拟提供了一种测试不同实验条件的简单方法，有助于发现调节生物系统的动力学。然而，这些模拟所需的计算能力往往超过普通台式计算机上可用的计算能力，因此需要昂贵的高性能计算解决方案。一个新兴的替代方案是以图形处理单元（GPGPU）为代表的通用科学计算，它以大约400美元的成本提供了一个小型计算机集群的能力。使用GPU进行计算需要开发特定的算法，因为编程范式与传统的基于CPU的计算有很大的不同。在本文中，我们回顾了最近的一些努力，利用GPU的处理能力，模拟生物系统。
The development of detailed, coherent, models of complex biological systems is recognized as a key requirement for integrating the increasing amount of experimental data. In addition, in-silico simulation of bio-chemical models provides an easy way to test different experimental conditions, helping in the discovery of the dynamics that regulate biological systems. However, the computational power required by these simulations often exceeds that available on common desktop computers and thus expensive high performance computing solutions are required. An emerging alternative is represented by general-purpose scientific computing on graphics processing units (GPGPU), which offers the power of a small computer cluster at a cost of similar to$400. Computing with a GPU requires the development of specific algorithms, since the programming paradigm substantially differs from traditional CPU-based computing. In this paper, we review some recent efforts in exploiting the processing power of GPUs for the simulation of biological systems.