论文标题
SIMD算法，用于检测任何顺序相互作用
A SIMD algorithm for the detection of epistatic interactions of any order
论文作者
论文摘要
上科斯是一种现象，其中表型结果取决于两个或多个基因座的遗传变异的相互作用，并且不能归因于对应于单个基因座的效应的添加剂组合。尽管威廉·贝特森（William Bateson）提出了这一概念已经有100多年了，但它仍然是一个积极研究的话题。定位上皮相互作用是一个计算上昂贵的挑战，涉及分析成倍增长的组合。该领域的作者已经诉诸了多种硬件体系结构以加快搜索的速度，但是几乎没有关注当前CPU在其说明中包含的向量说明。这项工作扩展了现有的三阶详尽算法，以支持任何顺序的上毒交互的搜索，并讨论了使用Intel Avx Interinsics组成搜索的不同功能的多个SIMD实现。使用GCC和英特尔编译器的结果表明，此处提出的512位显式矢量实现在评估的所有其他实现中都表现最好。在测试的情况下，提出的512位矢量化分别加速了GCC和Intel编译器的平均实现该算法的平均值7和12。
Epistasis is a phenomenon in which a phenotype outcome is determined by the interaction of genetic variation at two or more loci and it cannot be attributed to the additive combination of effects corresponding to the individual loci. Although it has been more than 100 years since William Bateson introduced this concept, it still is a topic under active research. Locating epistatic interactions is a computationally expensive challenge that involves analyzing an exponentially growing number of combinations. Authors in this field have resorted to a multitude of hardware architectures in order to speed up the search, but little to no attention has been paid to the vector instructions that current CPUs include in their instruction sets. This work extends an existing third-order exhaustive algorithm to support the search of epistasis interactions of any order and discusses multiple SIMD implementations of the different functions that compose the search using Intel AVX Intrinsics. Results using the GCC and the Intel compiler show that the 512-bit explicit vector implementation proposed here performs the best out of all of the other implementations evaluated. The proposed 512-bit vectorization accelerates the original implementation of the algorithm by an average factor of 7 and 12, for GCC and the Intel Compiler, respectively, in the scenarios tested.
