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首页> 外文期刊>IEEE/ACM transactions on computational biology and bioinformatics >Accelerating Sequence Alignments Based on FM-Index Using the Intel KNL Processor
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Accelerating Sequence Alignments Based on FM-Index Using the Intel KNL Processor

机译：使用英特尔KNL处理器基于FM索引加速序列对齐

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摘要

FM-index is a compact data structure suitable for fast matches of short reads to large reference genomes. The matching algorithm using this index exhibits irregular memory access patterns that cause frequent cache misses, resulting in a memory bound problem. This paper analyzes different FM-index versions presented in the literature, focusing on those computing aspects related to the data access. As a result of the analysis, we propose a new organization of FM-index that minimizes the demand for memory bandwidth, allowing a great improvement of performance on processors with high-bandwidth memory, such as the second-generation Intel Xeon Phi (Knights Landing, or KNL), integrating ultra high-bandwidth stacked memory technology. As the roofline model shows, our implementation reaches 95 percent of the peak random access bandwidth limit when executed on the KNL and almost all of the available bandwidth when executed on other Intel Xeon architectures with conventional DDR memory. In addition, the obtained throughput in KNL is much higher than the results reported for GPUs in the literature.
机译：FM-Index是一个紧凑的数据结构，适用于短读取的快速匹配到大参考基因组。使用此索引的匹配算法展示了不规则的内存访问模式，导致频繁缓存未命中，导致内存绑定问题。本文分析了文献中呈现的不同FM-Index版本，专注于与数据访问相关的计算方面。由于分析结果，我们提出了一个新的FM-索引组织，最大限度地减少对内存带宽的需求，从而提高了高带宽存储器的处理器上的性能，例如第二代英特尔Xeon Phi（骑士登陆或KNL），集成超高带宽堆叠的存储器技术。随着屋顶模型的表明，我们的实现达到了在KNL上执行的峰值随机接入带宽限制的95％，几乎所有可用带宽在具有传统DDR内存的其他英特尔Xeon架构上执行时。此外，所获得的KNL的产量远高于文献中GPU的结果。

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