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For an in-memory task, it dedicates all available CPU cores to the task, and allows parallelly scalable PRAM algorithms to retain the property,\n            <jats:italic>i.e.<\/jats:italic>\n            , the more cores are available, the less runtime is taken. We develop a graph partitioning and work scheduling strategy to accommodate subgraph I\/O, balance memory usage and reduce runtime, beyond traditional partitioners for multi-machine systems. Using real-life graphs, we empirically verify that Planar outperforms SOTA in-memory and out-of-core systems in efficiency and scalability.\n          <\/jats:p>","DOI":"10.14778\/3712221.3712240","type":"journal-article","created":{"date-parts":[[2025,4,7]],"date-time":"2025-04-07T18:03:04Z","timestamp":1744048984000},"page":"756-769","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A Single Machine System for Querying Big Graphs with PRAM"],"prefix":"10.14778","volume":"18","author":[{"given":"Yang","family":"Liu","sequence":"first","affiliation":[{"name":"Beihang University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenfei","family":"Fan","sequence":"additional","affiliation":[{"name":"Shenzhen Institute of Computing Sciences, China and Beihang University, China and University of Edinburgh, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuhao","family":"Liu","sequence":"additional","affiliation":[{"name":"Shenzhen Institute of Computing Sciences, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoke","family":"Zhu","sequence":"additional","affiliation":[{"name":"Beihang University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianxin","family":"Li","sequence":"additional","affiliation":[{"name":"Beihang University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,4,7]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"2024. 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