关键词: 非一致性访存, Bowtie 2, 适应性优化, 体系结构, 内存带宽, 最后一级缓存

Abstract: Bowtie 2, as one of the most widely used second-generation sequencing software in the field of bioinformatics, is characterized by its computational intensity. How to conduct adaptive optimization based on the architecture of multi-core platforms to improve parallel efficiency has become an urgent problem to be solved. This paper first analyzes the diversity of non-uniform memory access (NUMA) architectures and the structural bottlenecks of Bowtie 2 under various NUMA architectures, including memory access congestion and low last level cache hit rates. Then, based on the performance characteristics of Bowtie 2 on different NUMA platforms, optimizations are carried out in three aspects: index replication, memory allocation, and data partitioning, leading to the proposal of Bowtie 2- NUMA. Finally, experiments show that Bowtie 2-NUMA can achieve adaptive optimization based on the architecture for different computing platforms, thereby improving parallel efficiency.

Key words: non-uniform memory access (NUMA), Bowtie 2, adaptive optimization, computer architecture, memory bandwidth, last level cache (LLC)