减少模板计算中的数据组织和算术运算冗余
Reducing Redundancy in Data Organization and Arithmetic Calculation for Stencil Computations
摘要：
摘要空间计算是各种科学和工程应用中最重要的核心之一。各种工作都集中在向量化技术上，旨在利用核内数据并行。简而言之，它们要么引发数据对齐冲突，要么在与切片集成时损害数据局部性。在本文中，一种新的转置布局的设计，以保持在数据空间中的平铺数据的局部性，并减少数据重组的矢量化开销的同时。然后，我们提出了一种临时计算折叠的方法，旨在进一步减少冗余的算术计算，通过利用寄存器重用，减轻增加的寄存器压力，并推导推广与线性回归模型。在AVX-2和AVX-512 CPU上的实验结果表明，该方法具有较好的性能。
英文摘要：
Stencil computation is one of the most important kernels in various scientific and engineering applications. A variety of work has focused on vectorization techniques, aiming at exploiting the in-core data parallelism. Briefly, they either incur data alignment conflicts or hurt the data locality when integrated with tiling. In this paper, a novel transpose layout is devised to preserve the data locality for tiling in the data space and reduce the data reorganization overhead for vectorization simultaneously. We then propose an approach of temporal computation folding designed to further reduce the redundancy of arithmetic calculations by exploiting the register reuse, alleviating the increased register pressure, and deducing generalization with a linear regression model. Experimental results on the AVX-2 and AVX-512 CPUs show that our approach obtains a competitive performance.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
