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C2CU: A CUDA C Program Generator for Bulk Execution of a Sequential Algorithm

机译:C2CU:CUDA C程序生成器,用于批量执行顺序算法

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A sequential algorithm is oblivious if an address accessed at each time does not depend on input data. Many important tasks including matrix computation, signal processing, sorting, dynamic programming, and encryption/decryption can be performed by oblivious sequential algorithms. Bulk execution of a sequential algorithm is to execute it for many independent inputs in turn or in parallel. The main contribution of this paper is to develop a tool that generates a CUDA C program for the bulk execution of an oblivious sequential algorithm. More specifically, our tool automatically converts a C language program describing an oblivious sequential algorithm into a CUDA C program that performs the bulk execution of the C language program. Generated C programs can be executed in CUDA-enabled GPUs. We have implemented CUDA C programs for the bulk execution of bitonic sorting algorithm, Floyd-Warshall algorithm, and Montgomery modulo multiplication. Our implementations running on GeForce GTX Titan for the bulk execution can be 199 times faster for bitonic sort, 54 times faster for Floyd-Warshall algorithm, and 78 times faster for Montgomery modulo multiplication, over the implementations on a single Intel Xeon CPU.
机译:如果每次访问的地址不依赖于输入数据,则顺序算法将被忽略。许多重要的任务,包括矩阵计算,信号处理,分类,动态编程以及加密/解密,都可以通过遗忘的顺序算法来执行。批量执行顺序算法是针对许多独立输入依次或并行执行它。本文的主要贡献是开发一种工具,该工具可生成CUDA C程序,以批量执行遗忘的顺序算法。更具体地说,我们的工具会自动将描述遗忘顺序算法的C语言程序转换为执行C语言程序的批量执行的CUDA C程序。生成的C程序可以在启用CUDA的GPU中执行。我们已经实现了CUDA C程序,用于批量执行音调排序算法,Floyd-Warshall算法和Montgomery模乘法。与单个Intel Xeon CPU上的实现相比,我们在GeForce GTX Titan上运行以实现批量执行的实现可以比双比特排序快199倍,Floyd-Warshall算法快54倍,蒙哥马利模乘快78倍。

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