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

机译:通过沿波前展开展开优化最长公共子序列问题

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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:循环展开是一种循环转换,其中一些循环迭代被分组为超级迭代,以探索更多独立的指令并减少总循环开销。本文通过展开因子,超级迭代中的迭代次数和展开方向,要组合成超级迭代的迭代的选择来表征循环展开。在最长的常见子序列问题中,我们使用循环展开来最大程度地提高指令级并行度。为了增加超级迭代中独立指令的数量,我们使用线性调度来将同一波前(循环迭代空间中的超平面)上的迭代分组。然后,沿着波前展开循环,以确保同一超级迭代中的所有迭代都是独立的。最佳展开因子的选择基于以下假设:如果所有管道都饱和,则性能应该不会很差。提出了两个必要条件和一个满足最优性的充分条件,并将其用于找到最佳展开因子。总执行时间表示为算法参数,体系结构参数和展开因子的函数。该技术的基准比传统方法得分高1.475。

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