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It generates a data-aware and rule-aware execution plan on CPUs, for specifying how rules are evaluated, and develops a number of hardware-aware optimizations to achieve massive parallelism on GPUs.<\/jats:p>\n          <jats:p>Using real-life datasets, we show that HyperBlocker is at least 6.8\u00d7 and 9.1\u00d7 faster than prior CPU-powered distributed systems and GPU-based ER solvers, respectively. Better still, by combining HyperBlocker with the state-of-the-art ER matcher, we can speed up the overall ER process by at least 30% with comparable accuracy.<\/jats:p>","DOI":"10.14778\/3705829.3705847","type":"journal-article","created":{"date-parts":[[2025,2,28]],"date-time":"2025-02-28T23:21:06Z","timestamp":1740784866000},"page":"308-321","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["HyperBlocker: Accelerating Rule-Based Blocking in Entity Resolution Using GPUs"],"prefix":"10.14778","volume":"18","author":[{"given":"Xiaoke","family":"Zhu","sequence":"first","affiliation":[{"name":"Beihang University, China and Shenzhen Institute of Computing Sciences, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min","family":"Xie","sequence":"additional","affiliation":[{"name":"Shenzhen Institute of Computing Sciences, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ting","family":"Deng","sequence":"additional","affiliation":[{"name":"Beihang University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Meta Platforms, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,2,28]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"2021. 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