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On Optimizing the Longest Common Subsequence Problem by Loop Unrolling Along Wavefronts

机译:通过沿波前展开的循环优化最长的常见后续问题

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Loop unrolling is a loop transformation where a few loop iterations are grouped as a super iteration for exploring more independent instructions and to decrease the total loop overhead. This paper characterizes loop unrolling by the unrolling factor, the number of iterations in a super iteration and the unrolling direction, the choice of iterations to be grouped to form the super iteration. We use loop unrolling for maximizing instruction-level parallelism in the longest common subsequence problem. To increase the number of independent instructions in the super iteration, we use a linear schedule to group iterations on the same wave front, a hyper plane in the loop iteration space. Then, the loop is unrolled along the wave front which guarantees all iterations in the same super iteration are independent. The selection of the optimal unrolling factor is based on the assumption that if all the pipelines are saturated, the performance should not be bad. Two necessary conditions and a sufficient condition for optimality are presented and used to find the optimal unrolling factor. The total execution time is expressed as a function of algorithm parameters, architecture parameters and the unrolling factor. A benchmark of the technique scores a 1.475 speed-up over traditional methods.
机译:循环展开是一个循环变换,其中一些循环迭代被分组为超迭代,以便探索更多独立指令并减少总循环开销。本文表征了展开因子展开的循环,超迭代和展开方向的迭代次数,选择要分组的迭代选择以形成超迭代。我们使用循环展开,以便在最长的常见后续问题中最大化指令级并行性。为了增加超迭代中的独立指令的数量,我们使用线性计划来对同一波前沿进行分组迭代,在循环迭代空间中的超平面。然后,沿波前展开循环,保证相同的超迭代中的所有迭代是独立的。最佳展开因子的选择是基于假设,如果所有管道饱和,性能不应该是坏的。呈现并用于最佳令人效能性的两个必要条件和足够的条件来找到最佳的展开因子。总执行时间表示为算法参数,架构参数和展开因子的函数。技术的基准比传统方法的加速1.475。

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