物理学中的模拟通常需要考虑宇宙学和天体物理学、电磁学（例如，光传播 g 搜索“+fdtd +gpu”）和流体模拟、生物环境、大气等中的数千/数百万个粒子。 GPU可以利用宇宙中存在的并行性。硬件和软件已准备就绪（g-search Open-CL、CUDA）。你的办公桌上可以有一台超级计算机。在几乎所有模拟中，我们都可以使用并行推理：定义如何对一个组件的响应进行建模，并将其应用于以时间步长传播交互的所有组件。
在这里查看我的 PSE 答案以查看一个不错的下图是我的 GPU（300 个处理器）使用直接 N-Body 代码来模拟重力相互作用。
The simulation in Physics usually needs to consider thousands/millions of particles in cosmology and astrophysics, in Electromagnetic (e.g. in the light propagation g-search "+fdtd +gpu") and fluid simulations, in biological contexts, atmosphere, etc. The GPU can harness the parallelism that is present in the universe. The hardware and the software are ready (g-search Open-CL, CUDA). You can have a supercomputer in your desk. In almost all simulations we can use parallel reasoning: define how to model the response of one component and apply to all components propagating the interactions in time steps.
see my PSE-answer here to see a nice picture where my GPU(300 processors) was used to simulate gravitacional interactions using direct N-Body code.
一般来说，GPU 可用于并行计算（每个像素或每个事件），具有简单的 C 兼容（非面向对象）例程，例如 Fourier trafo、直方图等
It's quite a new field, but I've seen an application in astrophysics once.
Generally GPUs can be used for parallelizable calculations (per pixel or per event), with simple C-compatible (not object oriented) routines, e.g. fourier trafo, histograms, etc
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物理学中的模拟通常需要考虑宇宙学和天体物理学、电磁学（例如，光传播 g 搜索“+fdtd +gpu”）和流体模拟、生物环境、大气等中的数千/数百万个粒子。 GPU可以利用宇宙中存在的并行性。硬件和软件已准备就绪（g-search Open-CL、CUDA）。你的办公桌上可以有一台超级计算机。在几乎所有模拟中，我们都可以使用并行推理：定义如何对一个组件的响应进行建模，并将其应用于以时间步长传播交互的所有组件。
在这里查看我的 PSE 答案以查看一个不错的下图是我的 GPU（300 个处理器）使用直接 N-Body 代码来模拟重力相互作用。
The simulation in Physics usually needs to consider thousands/millions of particles in cosmology and astrophysics, in Electromagnetic (e.g. in the light propagation g-search "+fdtd +gpu") and fluid simulations, in biological contexts, atmosphere, etc. The GPU can harness the parallelism that is present in the universe. The hardware and the software are ready (g-search Open-CL, CUDA). You can have a supercomputer in your desk. In almost all simulations we can use parallel reasoning: define how to model the response of one component and apply to all components propagating the interactions in time steps.
see my PSE-answer here to see a nice picture where my GPU(300 processors) was used to simulate gravitacional interactions using direct N-Body code.
这是一个相当新的领域，但我曾经见过一次在天体物理学中的应用。
一般来说，GPU 可用于并行计算（每个像素或每个事件），具有简单的 C 兼容（非面向对象）例程，例如 Fourier trafo、直方图等
It's quite a new field, but I've seen an application in astrophysics once.
Generally GPUs can be used for parallelizable calculations (per pixel or per event), with simple C-compatible (not object oriented) routines, e.g. fourier trafo, histograms, etc