{"id":3610,"date":"2025-11-08T12:02:51","date_gmt":"2025-11-08T12:02:51","guid":{"rendered":"https:\/\/blogs.qub.ac.uk\/dipsa\/?p=3610"},"modified":"2026-03-09T05:46:44","modified_gmt":"2026-03-09T05:46:44","slug":"paragrapher-a-parallel-and-distributed-graph-loading-library-for-large-scale-compressed-graphs-bigdata25","status":"publish","type":"post","link":"https:\/\/blogs.qub.ac.uk\/dipsa\/paragrapher-a-parallel-and-distributed-graph-loading-library-for-large-scale-compressed-graphs-bigdata25\/","title":{"rendered":"ParaGrapher: A Parallel and Distributed Graph Loading Library for Large-Scale Compressed Graphs &#8211; BigData&#8217;25 (Short Paper)"},"content":{"rendered":"\n<p><br><strong>DOI: <\/strong><a href=\"https:\/\/doi.org\/10.1109\/BigData66926.2025.11401782\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>10.1109\/BigData66926.2025.11401782<\/strong><\/a><\/p>\n\n\n\n<p class=\"has-text-align-justify\">Whereas the literature describes an increasing number of graph algorithms, loading graphs remains a time-consuming component of the end-to-end execution time. Graph frameworks often rely on custom graph storage formats, that are not optimized for efficient loading of large-scale graph datasets. Furthermore, graph loading is often not optimized as it is time-consuming to implement.<br> <br>This shows a demand for high-performance libraries capable of efficiently loading graphs to (i) accelerate designing new graph algorithms, (ii) to evaluate the contributions across a wide range of graph datasets, and (iii) to facilitate easy and fast comparisons across different graph frameworks.<br><br>We present ParaGrapher, a library for loading large-scale compressed graphs in parallel and distributed graph frameworks. ParaGrapher supports (a) loading the graph while the caller is blocked and (b) interleaving graph loading with graph processing. ParaGrapher is designed to support loading graphs in shared-memory, distributed-memory, and out-of-core graph processing. <br><br>We explain the design of ParaGrapher and present a performance model of graph decompression. Our evaluation shows that ParaGrapher delivers up to 3.2 times speedup in loading and up to 5.2 times speedup in end-to-end execution (i.e., through interleaved loading and execution).<\/p>\n\n\n\n<h2 class=\"wp-block-heading has-medium-font-size\"><strong>Source Code<\/strong><\/h2>\n\n\n\n<p style=\"font-size:16px\"><strong><a href=\"https:\/\/github.com\/DIPSA-QUB\/ParaGrapher\">https:\/\/github.com\/DIPSA-QUB\/ParaGrapher<\/a><\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading has-medium-font-size\"><strong>API Documentation<\/strong><\/h2>\n\n\n\n<p>Please refer to the Wiki, <a href=\"https:\/\/github.com\/DIPSA-QUB\/ParaGrapher\/wiki\/API-Documentation\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/github.com\/DIPSA-QUB\/ParaGrapher\/wiki\/API-Documentation<\/a>, or download the PDF file using <a href=\"https:\/\/github.com\/DIPSA-QUB\/ParaGrapher\/raw\/main\/doc\/api.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/github.com\/DIPSA-QUB\/ParaGrapher\/raw\/main\/doc\/api.pdf<\/a> .<\/p>\n\n\n\n<p class=\"has-text-align-justify\"><\/p>\n\n\n\n<div class=\"wp-block-jetpack-slideshow aligncenter\" data-autoplay=\"true\" data-delay=\"5\" data-effect=\"slide\"><div class=\"wp-block-jetpack-slideshow_container swiper\"><ul class=\"wp-block-jetpack-slideshow_swiper-wrapper swiper-wrapper\"><li class=\"wp-block-jetpack-slideshow_slide swiper-slide\"><figure><img fetchpriority=\"high\" decoding=\"async\" width=\"1000\" height=\"563\" alt=\"\" class=\"wp-block-jetpack-slideshow_image wp-image-3616\" data-id=\"3616\" src=\"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-01.png\" srcset=\"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-01.png 1000w, https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-01-300x169.png 300w, 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https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-07-768x432.png 768w, https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-07-500x282.png 500w\" sizes=\"(max-width: 1000px) 100vw, 1000px\" \/><figcaption class=\"wp-block-jetpack-slideshow_caption gallery-caption\"><\/figcaption><\/figure><\/li><li class=\"wp-block-jetpack-slideshow_slide swiper-slide\"><figure><img loading=\"lazy\" decoding=\"async\" width=\"1000\" height=\"563\" alt=\"\" class=\"wp-block-jetpack-slideshow_image wp-image-3622\" data-id=\"3622\" src=\"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-08.png\" srcset=\"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-08.png 1000w, https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-08-300x169.png 300w, https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-08-768x432.png 768w, https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-08-500x282.png 500w\" sizes=\"(max-width: 1000px) 100vw, 1000px\" \/><figcaption class=\"wp-block-jetpack-slideshow_caption gallery-caption\"><\/figcaption><\/figure><\/li><li class=\"wp-block-jetpack-slideshow_slide swiper-slide\"><figure><img loading=\"lazy\" decoding=\"async\" width=\"1000\" height=\"563\" alt=\"\" class=\"wp-block-jetpack-slideshow_image wp-image-3623\" data-id=\"3623\" src=\"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-09.png\" srcset=\"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-09.png 1000w, https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-09-300x169.png 300w, https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-09-768x432.png 768w, https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-09-500x282.png 500w\" sizes=\"(max-width: 1000px) 100vw, 1000px\" \/><figcaption class=\"wp-block-jetpack-slideshow_caption gallery-caption\"><\/figcaption><\/figure><\/li><li class=\"wp-block-jetpack-slideshow_slide swiper-slide\"><figure><img loading=\"lazy\" decoding=\"async\" width=\"1000\" height=\"563\" alt=\"\" class=\"wp-block-jetpack-slideshow_image wp-image-3624\" data-id=\"3624\" src=\"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-10.png\" srcset=\"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-10.png 1000w, https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-10-300x169.png 300w, https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-10-768x432.png 768w, https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/paragrapher-bigdata25-10-500x282.png 500w\" sizes=\"(max-width: 1000px) 100vw, 1000px\" \/><figcaption class=\"wp-block-jetpack-slideshow_caption gallery-caption\"><\/figcaption><\/figure><\/li><\/ul><a class=\"wp-block-jetpack-slideshow_button-prev swiper-button-prev swiper-button-white\" role=\"button\"><\/a><a class=\"wp-block-jetpack-slideshow_button-next swiper-button-next swiper-button-white\" role=\"button\"><\/a><a aria-label=\"Pause Slideshow\" class=\"wp-block-jetpack-slideshow_button-pause\" role=\"button\"><\/a><div class=\"wp-block-jetpack-slideshow_pagination swiper-pagination swiper-pagination-white\"><\/div><\/div><\/div>\n\n\n\n<p class=\"has-medium-font-size\"><strong>BibTex<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>@INPROCEEDINGS{paragrapher-bigdata,\n  author={Koohi Esfahani, Mohsen  and Tauhidi, Syed Ibtisam and D'Antonio, Marco and Mai, Thai Son and Vandierendonck, Hans},\n  booktitle={2025 IEEE International Conference on Big Data (BigData)}, \n  title={ParaGrapher: A Parallel and Distributed Graph Loading Library for Large-Scale Compressed Graphs}, \n  year={2025},\n  volume={},\n  number={},\n  pages={255-260},\n  doi={10.1109\/BigData66926.2025.11401782}\n}<\/code><\/pre>\n\n\n\n<p class=\"has-medium-font-size\"><strong>Related Posts &amp; Source Code<\/strong><\/p>\n\n\n\n<p style=\"font-size:16px\"><a href=\"https:\/\/blogs.qub.ac.uk\/DIPSA\/ParaGrapher\"><strong>ParaGrapher Web Page<\/strong><\/a> <\/p>\n\n\n<ul class=\"wp-block-latest-posts__list has-dates wp-block-latest-posts\"><li><div class=\"wp-block-latest-posts__featured-image alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"150\" src=\"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/1-150x150.jpg\" class=\"attachment-thumbnail size-thumbnail wp-post-image\" alt=\"\" style=\"max-width:75px;max-height:75px;\" \/><\/div><a class=\"wp-block-latest-posts__post-title\" href=\"https:\/\/blogs.qub.ac.uk\/dipsa\/paragrapher-a-parallel-and-distributed-graph-loading-library-for-large-scale-compressed-graphs-bigdata25\/\">ParaGrapher: A Parallel and Distributed Graph Loading Library for Large-Scale Compressed Graphs &#8211; BigData&#8217;25 (Short Paper)<\/a><time datetime=\"2025-11-08T12:02:51+00:00\" class=\"wp-block-latest-posts__post-date\">8 November 2025<\/time><\/li>\n<li><div class=\"wp-block-latest-posts__featured-image alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"150\" src=\"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2024\/12\/1-150x150.jpg\" class=\"attachment-thumbnail size-thumbnail wp-post-image\" alt=\"\" style=\"max-width:75px;max-height:75px;\" \/><\/div><a class=\"wp-block-latest-posts__post-title\" href=\"https:\/\/blogs.qub.ac.uk\/dipsa\/accelerating-loading-webgraphs-in-paragrapher\/\">Accelerating Loading WebGraphs in ParaGrapher<\/a><time datetime=\"2024-12-02T05:51:29+00:00\" class=\"wp-block-latest-posts__post-date\">2 December 2024<\/time><\/li>\n<li><div class=\"wp-block-latest-posts__featured-image alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"150\" src=\"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2024\/05\/fern-150x150.jpg\" class=\"attachment-thumbnail size-thumbnail wp-post-image\" alt=\"\" style=\"max-width:75px;max-height:75px;\" \/><\/div><a class=\"wp-block-latest-posts__post-title\" href=\"https:\/\/blogs.qub.ac.uk\/dipsa\/selective-parallel-loading-of-large-scale-compressed-graphs-with-paragrapher\/\">Selective Parallel Loading of Large-Scale Compressed Graphs with ParaGrapher &#8211; arXiv Version<\/a><time datetime=\"2024-05-01T05:44:14+01:00\" class=\"wp-block-latest-posts__post-date\">1 May 2024<\/time><\/li>\n<li><div class=\"wp-block-latest-posts__featured-image alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"150\" src=\"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2024\/04\/passerine-150x150.jpg\" class=\"attachment-thumbnail size-thumbnail wp-post-image\" alt=\"\" style=\"max-width:75px;max-height:75px;\" \/><\/div><a class=\"wp-block-latest-posts__post-title\" href=\"https:\/\/blogs.qub.ac.uk\/dipsa\/an-evaluation-of-bandwidth-of-different-storage-types-hdd-vs-ssd-vs-lustrefs-for-different-block-sizes-and-different-read-methods-mmap-vs-pread-vs-read\/\">An Evaluation of Bandwidth of Different Storage Types (HDD vs. SSD vs. LustreFS) for Different Block Sizes and Different Parallel Read Methods (mmap vs pread vs read)<\/a><time datetime=\"2024-04-20T09:48:10+01:00\" class=\"wp-block-latest-posts__post-date\">20 April 2024<\/time><\/li>\n<li><div class=\"wp-block-latest-posts__featured-image alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"150\" src=\"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2024\/02\/loriini-150x150.jpg\" class=\"attachment-thumbnail size-thumbnail wp-post-image\" alt=\"\" style=\"max-width:75px;max-height:75px;\" \/><\/div><a class=\"wp-block-latest-posts__post-title\" href=\"https:\/\/blogs.qub.ac.uk\/dipsa\/paragrapher-integrated-to-laganlighter\/\">ParaGrapher Integrated to LaganLighter<\/a><time datetime=\"2024-02-16T08:29:26+00:00\" class=\"wp-block-latest-posts__post-date\">16 February 2024<\/time><\/li>\n<li><div class=\"wp-block-latest-posts__featured-image alignleft\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"150\" src=\"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2024\/02\/poplar2-150x150.jpg\" class=\"attachment-thumbnail size-thumbnail wp-post-image\" alt=\"\" style=\"max-width:75px;max-height:75px;\" \/><\/div><a class=\"wp-block-latest-posts__post-title\" href=\"https:\/\/blogs.qub.ac.uk\/dipsa\/paragrapher-source-code-for-webgraph-types\/\">ParaGrapher Source Code For WebGraph Types<\/a><time datetime=\"2024-02-16T08:13:13+00:00\" class=\"wp-block-latest-posts__post-date\">16 February 2024<\/time><\/li>\n<\/ul>","protected":false},"excerpt":{"rendered":"<p>DOI: 10.1109\/BigData66926.2025.11401782 Whereas the literature describes an increasing number of graph algorithms, loading graphs remains a time-consuming component of the end-to-end execution time. Graph frameworks often rely on custom graph storage formats, that are not optimized for efficient loading of &hellip; <a href=\"https:\/\/blogs.qub.ac.uk\/dipsa\/paragrapher-a-parallel-and-distributed-graph-loading-library-for-large-scale-compressed-graphs-bigdata25\/\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":1315,"featured_media":3613,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[119],"tags":[34,35,38,64,122,66,65,19,123,124],"class_list":["post-3610","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-paragrapher","tag-algorithm-design-and-engineering","tag-graph-processing","tag-high-performance-computing","tag-high-performance-graph-processing","tag-parallel-io","tag-real-world-graphs","tag-sequence-similarity-graphs","tag-source-code","tag-storage","tag-trillion-scale-graph-datasets"],"jetpack_featured_media_url":"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-content\/uploads\/sites\/14\/2025\/11\/1.jpg","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-json\/wp\/v2\/posts\/3610","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-json\/wp\/v2\/users\/1315"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-json\/wp\/v2\/comments?post=3610"}],"version-history":[{"count":11,"href":"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-json\/wp\/v2\/posts\/3610\/revisions"}],"predecessor-version":[{"id":3669,"href":"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-json\/wp\/v2\/posts\/3610\/revisions\/3669"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-json\/wp\/v2\/media\/3613"}],"wp:attachment":[{"href":"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-json\/wp\/v2\/media?parent=3610"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-json\/wp\/v2\/categories?post=3610"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.qub.ac.uk\/dipsa\/wp-json\/wp\/v2\/tags?post=3610"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}