CMacIonize 2.0：一种新的基于任务的蒙特卡罗辐射传递方法
CMacIonize 2.0: a novel task-based approach to Monte Carlo radiation transfer
摘要：
蒙特卡罗辐射转移（MCRT）是一种广泛使用的模拟辐射与介质相互作用的技术，在天体物理建模和将这些模型与观测进行比较时起着重要作用。（目的）在这项工作中，我们提出了一种新的方法来MCRT，解决传统的MCRT算法，这阻碍了最佳性能的MCRT模拟现代硬件上的复杂的存储器架构的挑战性的存储器访问模式。（方法）我们将MCRT光子包生命周期重新表述为基于任务的算法，从而将计算分解为并发执行的小任务。光子包存储在中间缓冲区中，任务通过计算域的一小部分传播光子包，在此过程中将它们从一个缓冲区移动到另一个缓冲区。（结果）在光电离MCRT程序CMacIonize 2.0中实现了新算法，结果表明，将MCRT网格分解为小块，在光子包传播阶段（构成MCRT算法的主体），由于更好地利用了内存缓存，导致了显著的性能增益。我们的新算法比同等的传统算法快2到4倍，并显示出良好的可扩展性，最多可扩展到30个线程。我们简要地讨论了我们的新算法可以调整或扩展到其他天体物理MCRT应用。（结论）我们表明，优化内存绑定算法（如MCRT）的内存访问模式可以产生显着的性能增益。
英文摘要：
(Context) Monte Carlo radiative transfer (MCRT) is a widely used technique to model the interaction between radiation and a medium, and plays an important role in astrophysical modelling and when comparing those models with observations. (Aims) In this work, we present a novel approach to MCRT that addresses the challenging memory access patterns of traditional MCRT algorithms, which hinder optimal performance of MCRT simulations on modern hardware with a complex memory architecture. (Methods) We reformulate the MCRT photon packet life cycle as a task-based algorithm, whereby the computation is broken down into small tasks that are executed concurrently. Photon packets are stored in intermediate buffers, and tasks propagate photon packets through small parts of the computational domain, moving them from one buffer to another in the process. (Results) Using the implementation of the new algorithm in the photoionization MCRT code CMacIonize 2.0, we show that the decomposition of the MCRT grid into small parts leads to a significant performance gain during the photon packet propagation phase, which constitutes the bulk of an MCRT algorithm, as a result of better usage of memory caches. Our new algorithm is a factor 2 to 4 faster than an equivalent traditional algorithm and shows good strong scaling up to 30 threads. We briefly discuss how our new algorithm could be adjusted or extended to other astrophysical MCRT applications. (Conclusions) We show that optimising the memory access patterns of a memory-bound algorithm such as MCRT can yield significant performance gains.
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