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. 2022 Nov 30;23:513. doi: 10.1186/s12859-022-05052-8

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© The Author(s) 2022

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 2 — A Memory (red) and speed (blue) metrics of running metaSPAdes (top) and MEGAHIT (bottom) on the Wastewater metagenome dataset. The percentage of PMem of the total memory (DRAM+PMem) is shown on the horizontal axis, while the speed cost in folds is shown on the left vertical axis, whereas the amount of PMem used in GB is shown on the right vertical axis. For each memory configuration, we ran the pipeline twice and showed the average results (speed and PMem amounts). B Comparison of MetaHipMer2, MEGAHIT, and metaSPAdes running on the Wastewater metagenomics dataset. All three assemblers were run using 100% PMem. The total time of the wall clock (in minutes) is shown in blue, and the maximum memory consumption (in GB) is shown in red