Fourth-Order Exhaustive Epistasis Detection for the xPU Era.

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.