首页> 外文期刊>International Journal of Networking and Computing >Bulk execution of Euclidean algorithms on the CUDA-enabled GPU
【24h】

Bulk execution of Euclidean algorithms on the CUDA-enabled GPU

机译:在支持CUDA的GPU上批量执行Euclidean算法

获取原文
获取外文期刊封面目录资料

摘要

The bulk execution of a sequential algorithm is to execute it for many different inputs in turn or at the same time. A sequential algorithm is oblivious if the address accessed at each time unit is independent of the input. It is known that the bulk execution of an oblivious sequential algorithm can be implemented to run on a GPU very efficiently. The main purpose of our work is to implement the bulk execution of a Euclidean algorithm computing the GCD (Greatest Common Divisor) of two large numbers in a GPU. We first present a new efficient Euclidean algorithm that we call the Approximate Euclidean algorithm. The idea of the Approximate Euclidean algorithm is to compute an approximation of quotient by just one 64-bit division and to use it for reducing the number of iterations of the Euclidean algorithm. Unfortunately, the Approximate Euclidean algorithm is not oblivious. To show that the bulk execution of the Approximate Euclidean algorithm can be implemented efficiently in the GPU, we introduce a semi-oblivious sequential algorithms, which is almost oblivious. We show that the Approximate Euclidean algorithm can be implemented as a semi-oblivious algorithm. The experimental results show that our parallel implementation of the Approximate Euclidean algorithm for 1024- bit integers running on GeForce GTX Titan X GPU is 90 times faster than the Intel Xeon CPU implementation.?
机译:顺序算法的批量执行是依次或同时针对许多不同的输入执行该算法。如果在每个时间单位访问的地址独立于输入,那么顺序算法将被忽略。众所周知,遗忘的顺序算法的批量执行可以实现为非常高效地在GPU上运行。我们工作的主要目的是在GPU中实现欧几里德算法的批量执行,该算法计算两个大数的GCD(最大公约数)。我们首先提出一种新的高效欧几里得算法,我们将其称为近似欧几里得算法。近似欧几里德算法的思想是仅用一个64位除法来计算商的近似值,并将其用于减少欧几里德算法的迭代次数。不幸的是,近似欧几里得算法并不是忽略不计的。为了说明可以在GPU中有效地实现近似欧几里得算法的批量执行,我们引入了一个半遗忘的顺序算法,该算法几乎是遗忘的。我们表明,近似欧几里得算法可以实现为半遗忘算法。实验结果表明,对于在GeForce GTX Titan X GPU上运行的1024位整数的近似欧几里得算法的并行实现,比Intel Xeon CPU的实现快90倍。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号