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A Performance Study of CUDA UVM versus Manual Optimizations in a Real-World Setup: Application to a Monte Carlo Wave-Particle Event-Based Interaction Model

机译:实际设置中CUDA UVM与手动优化的性能研究:应用于基于蒙特卡罗波粒事件的交互模型

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The performance of a Monte Carlo model for the simulation of electromagnetic wave propagation in particle-filled atmospheres has been conducted for different CUDA versions and design approaches. The proposed algorithm exhibits a high degree of parallelism, which allows favorable implementation in a GPU. Practical implementation aspects of the model have been also explained and their impact assessed, such as the use of the different types of memories present in a GPU. A number of setups have been chosen in order to compare performance for manually optimized versus Unified Virtual Memory (UVM) implementations for different CUDA versions. Features and relative performance impact of the different options have been discussed, extracting practical hints and rules useful to speed up CUDA programs.
机译:对于不同的CUDA版本和设计方法,已经进行了用于模拟电磁波在充满粒子的气氛中传播的蒙特卡洛模型的性能。所提出的算法表现出高度的并行性,从而可以在GPU中实现良好的实现。还说明了模型的实际实现方面,并评估了其影响,例如使用GPU中存在的不同类型的内存。为了比较手动优化的性能和针对不同CUDA版本的统一虚拟内存(UVM)实现的性能,已选择了许多设置。讨论了不同选项的功能和相对性能影响,提取了有助于加快CUDA程序的实用提示和规则。

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