J Biomed Opt. 2012 Sep;17(9):90504-1. doi: 10.1117/1.JBO.17.9.090504.
In the framework of further development of the unified approach of photon migration in complex turbid media, such as biological tissues we present a peer-to-peer (P2P) Monte Carlo (MC) code. The object-oriented programming is used for generalization of MC model for multipurpose use in various applications of biomedical optics. The online user interface providing multiuser access is developed using modern web technologies, such as Microsoft Silverlight, ASP.NET. The emerging P2P network utilizing computers with different types of compute unified device architecture-capable graphics processing units (GPUs) is applied for acceleration and to overcome the limitations, imposed by multiuser access in the online MC computational tool. The developed P2P MC was validated by comparing the results of simulation of diffuse reflectance and fluence rate distribution for semi-infinite scattering medium with known analytical results, results of adding-doubling method, and with other GPU-based MC techniques developed in the past. The best speedup of processing multiuser requests in a range of 4 to 35 s was achieved using single-precision computing, and the double-precision computing for floating-point arithmetic operations provides higher accuracy.
在进一步发展复杂混浊介质(如生物组织)中光子迁移的统一方法的框架内,我们提出了一种点对点 (P2P) 蒙特卡罗 (MC) 代码。面向对象编程用于 MC 模型的推广,以便在生物医学光学的各种应用中多用途使用。使用现代网络技术(如 Microsoft Silverlight、ASP.NET)开发了提供多用户访问的在线用户界面。利用具有不同类型的计算统一设备架构功能的图形处理单元 (GPU) 的新兴 P2P 网络,用于加速和克服多用户访问在线 MC 计算工具带来的限制。通过将模拟的漫反射和通量率分布结果与已知分析结果、添加-加倍方法的结果以及过去开发的其他基于 GPU 的 MC 技术进行比较,验证了所开发的 P2P MC。使用单精度计算可实现处理多用户请求的最佳加速范围为 4 到 35 秒,而用于浮点数运算的双精度计算可提供更高的精度。