检测任意阶上位相互作用的SIMD算法
A SIMD algorithm for the detection of epistatic interactions of any order
摘要：
上位性是一种现象，其中表型结果由两个或多个基因座上的遗传变异的相互作用决定，并且不能归因于对应于单个基因座的效应的加性组合。虽然从威廉·贝特森提出这一概念到现在已经过去了100多年，但它仍然是一个正在积极研究的话题。定位上位相互作用是一个计算上昂贵的挑战，涉及分析指数增长的组合数量。该领域的作者已经采用了多种硬件架构来加速搜索，但很少或根本没有注意到当前CPU在其指令集中包含的向量指令。这项工作扩展了现有的三阶穷举算法，以支持搜索任何顺序的上位交互，并讨论了使用英特尔AVX Intrinsics组成搜索的不同函数的多个SIMD实现。使用GCC和Intel编译器的结果表明，这里提出的512位显式向量实现在所有其他评估的实现中表现最好。建议的512位矢量化加速算法的原始实现的平均因子为7和12，分别为GCC和英特尔英特尔®，在测试的情况下。
英文摘要：
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.
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