Fourth-Order Exhaustive Epistasis Detection for the xPU Era
Fourth-Order Exhaustive Epistasis Detection for the xPU Era
复制标题
xPU 时代的四阶详尽上位检测
DOI：
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
L. Sousa
中科院分区：
文献类型：
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作者：
Ricardo Nobre;A. Ilic;Sergio Santander;L. Sousa
针对现代异构系统的高效并行算法的研究可以为生物信息学家提供新的机制来发现遗传、表型和环境之间的关系。本文提出了一种针对现代异构系统的四阶穷举，即尽可能精确的上位性检测方法。在Data Parallel C++ / SYCL中实现，所提出的方法依赖于围绕开放标准构建的技术和工具，使其能够针对不同类型的架构和设备。作为一种手段，以显示与来自不同来源的硬件的互操作性，我们已经包括从不同的系统上执行获得的性能结果。按样本数量缩放，所提出的方法在具有Gen9.5，Gen 12和Turing架构的GPU上实现了每秒处理高达236，472或487兆quads SNP的每个GPU流核心的性能。该度量针对结合不同考虑的优化的不同实现变体报告。所提出的方法能够针对各种CPU和GPU设备，使更多的用户能够访问高吞吐量上位检测软件。
The investigation of highly-efficient parallel algorithms targeting modern heterogeneous systems can provide bioinformaticians new mechanisms to find relations between genetics, phenotype and environment. This paper proposes an approach for fourth-order exhaustive, i.e. as precise as possible, epistasis detection targeting modern heterogeneous systems. Being implemented in Data Parallel C++ / SYCL, the proposed approach relies on technologies and tools built around open standards, making it able to target different types of architectures and devices. As a means to show interoperability with hardware from different sources, we have included performance results obtained from execution on different systems. Scaled to the number of samples, the proposed approach achieved a performance per GPU stream core of up to 236, 472 or 487 mega quads of SNPs processed per second, on GPUs with the Gen9.5, Gen12 and Turing architectures. This metric is reported for different implementation variants combining different considered optimizations. The proposed approach is able to target a wide range of CPU and GPU devices, enabling more users to access high-throughput epistasis detection software.
影响因子：
3.3
作者：
Gonzalez-Dominguez, Jorge;Schmidt, Bertil
通讯作者：
Schmidt, Bertil
影响因子：
4
作者：
Sun, Jiya;Song, Fuhai;Lei, Hongxing
通讯作者：
Lei, Hongxing