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An efficient algorithm for communication set generation of data parallel programs with block-cyclic distribution

机译:具有块循环分布的数据并行程序通信集生成的高效算法

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Data parallel programming languages, such as High Performance Fortran, are widely regarded as a promising means for writing portable programs for distributed-memory machines. In this paper, we present a new algorithm for computing the communication sets in array section movements with block-cyclic (cyclic (k) in HPF) distribution. Our framework can handle multi-level alignments, multi-dimensional arrays, array intrinsic functions, affine indices and axis exchanges in the array subscript. Instead of employing the linear diophantine equation solver, a new algorithm which does not rely on the linear diophantine equation solver to calculate communication sets is proposed. We use formal proof and experimental results to show that it is more efficient than previous solutions to the same problem. Another important contribution of this paper is that we prove that the compiler is able to compute efficiently the communication sets of block-cyclic distribution as long as the block sizes of the arrays are set to be identical or the lowest common multiple (LCM) of block sizes is not a huge integer. We demonstrate it by thorough complexity analyses and extensive experimental results.
机译:诸如高性能Fortran之类的数据并行编程语言被广泛认为是为分布式内存计算机编写可移植程序的一种有前途的手段。在本文中,我们提出了一种新算法,用于计算具有块循环(HPF中的循环(k))分布的数组部分运动中的通信集。我们的框架可以处理数组下标中的多级对齐,多维数组,数组内在函数,仿射索引和轴交换。提出了一种新的算法,该算法不使用线性二阶方程方程求解器,而是使用线性二阶方程方程求解器来计算通信集。我们使用形式证明和实验结果表明,它比以前的解决方案更有效。本文的另一个重要贡献是,我们证明了只要数组的块大小设置为相同或块的最小公倍数(LCM),编译器就能有效地计算块循环分布的通信集。大小不是一个很大的整数。我们通过全面的复杂性分析和广泛的实验结果证明了这一点。

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