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An efficient implementation of Bailey and Borwein’s algorithm for parallel random number generation on graphics processing units

机译:Bailey和Borwein算法的有效实现,用于在图形处理单元上并行生成随机数

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Pseudorandom number generators are required for many computational tasks, such as stochastic modelling and simulation. This paper investigates the serial and parallel implementation of a Linear Congruential Generator for Graphics Processing Units (GPU) based on the binary representation of the normal number (alpha _{2,3}). We adapted two methods of modular reduction which allowed us to perform most operations in 64-bit integer arithmetic, improving on the original implementation based on 106-bit double-double operations, which resulted in four-fold increase in efficiency. We found that our implementation is faster than existing methods in literature, and our generation rate is close to the limiting rate imposed by the efficiency of writing to a GPU’s global memory.
机译:伪随机数生成器是许多计算任务(例如随机建模和仿真)所必需的。本文研究了基于常规数(alpha _ {2,3})的二进制表示形式的图形处理单元(GPU)线性同余生成器的串行和并行实现。我们采用了两种模块化的简化方法,使我们能够以64位整数算术执行大多数运算,并改进了基于106位double-double运算的原始实现,从而使效率提高了四倍。我们发现我们的实现比文献中的现有方法要快,并且我们的生成速率接近于写入GPU全局内存的效率所施加的极限速率。

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