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Optimization of SAMtools sorting using OpenMP tasks


SAMtools is a widely-used genomics application for post-processing high-throughput sequence alignment data. Such sequence alignment data are commonly sorted to make downstream analysis more efficient. However, this sorting process itself can be computationally- and I/O-intensive: high-throughput sequence alignment files in the de facto standard binary alignment/map (BAM) format can be many gigabytes in size, and may need to be decompressed before sorting and compressed afterwards. As a result, BAM-file sorting can be a bottleneck in genomics workflows. This paper describes a case study on the performance analysis and optimization of SAMtools for sorting large BAM files. OpenMP task parallelism and memory optimization techniques resulted in a speedup of 5.9X versus the upstream SAMtools 1.3.1 for an internal (in-memory) sort of 24.6 GiB of compressed BAM data (102.6 GiB uncompressed) with 32 processor cores, while a 1.98X speedup was achieved for an external (out-of-core) sort of a 271.4 GiB BAM file.

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    This check could occur after task generation and before returning from the routine; however, the implementation did not consistently perform as well in practice, possibly due to an undetermined effect on task scheduling.


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This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

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Correspondence to Nathan T. Weeks.

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Weeks, N.T., Luecke, G.R. Optimization of SAMtools sorting using OpenMP tasks. Cluster Comput 20, 1869–1880 (2017).

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  • Bioinformatics
  • High-throughput sequencing
  • OpenMP
  • Sorting
  • Burst buffer