clrng：R语言中用于GPU并行随机数生成的工具集
clrng: A tool set for parallel random numbergeneration on GPUs in R
AI总结：
本研究推出R语言包clrng，依托gpuR包与clRNG库实现GPU并行随机数生成，支持可复现研究、适配交互中断场景，可改善R的计算性能短板，且内核灵活可移植。
摘要：
我们介绍R语言包clrng，它依托gpuR包，能够借助clRNG（OpenCL）库在图形处理单元（GPU）上并行生成随机数。利用GPU进行并行处理可加速计算密集型任务，与R语言结合后，能大幅改善R在运行速度、内存使用和计算模式方面的短板。clrng通过为GPU和CPU上的随机数流设置初始随机种子，支持可复现研究，因此可加速多种类型的统计模拟与建模。即便以临时交互方式使用R、会话被中断后再恢复，clrng中的随机数生成器也能保证并行样本相互独立。该包具备可移植性与灵活性，开发者可将其随机数生成内核用于各类其他用途与应用场景。
英文摘要：
We introduce the R package clrng which leverages the gpuR package and is able to generate random numbers in parallel on a Graphics Processing Unit (GPU) with the clRNG (OpenCL) library. Parallel processing with GPU's can speed up computationally intensive tasks, which when combined with R, it can largely improve R's downsides in terms of slow speed, memory usage and computation mode. clrng enables reproducible research by setting random initial seeds for streams on GPU and CPU, and can thus accelerate several types of statistical simulation and modelling. The random number generator in clrng guarantees independent parallel samples even when R is used interactively in an ad-hoc manner, with sessions being interrupted and restored. This package is portable and flexible, developers can use its random number generation kernel for various other purposes and applications.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
