Resumen: 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% of the peak random access bandwidth limit when executed on the KNL and almost all 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. IEEE Idioma: Inglés DOI: 10.1109/TCBB.2018.2884701 Año: 2020 Publicado en: IEEE-ACM Transactions on Computational Biology and Bioinformatics 17, 4 (2020), 1093-1104 ISSN: 1545-5963 Factor impacto JCR: 3.71 (2020) Categ. JCR: STATISTICS & PROBABILITY rank: 15 / 125 = 0.12 (2020) - Q1 - T1 Categ. JCR: MATHEMATICS, INTERDISCIPLINARY APPLICATIONS rank: 18 / 108 = 0.167 (2020) - Q1 - T1 Categ. JCR: BIOCHEMICAL RESEARCH METHODS rank: 26 / 77 = 0.338 (2020) - Q2 - T2 Categ. JCR: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS rank: 46 / 112 = 0.411 (2020) - Q2 - T2 Factor impacto SCIMAGO: 0.745 - Applied Mathematics (Q2) - Genetics (Q2) - Biotechnology (Q2)