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Specifically, we design a succinct storage format for tensors to represent graph topology effectively and compose graph query operations using tensor computation on batches of vertices. We have developed TenGraph, our PyTorch-based prototype, and evaluated it on graph query benchmark workloads in comparison with a variety of CPU- and GPU-based systems. Our experimental results show that TenGraph not only achieves a speedup of 50-100 times on the GPU over the CPU but also outperforms the other CPU- and GPU-based systems significantly.<\/jats:p>","DOI":"10.14778\/3704965.3704967","type":"journal-article","created":{"date-parts":[[2025,2,18]],"date-time":"2025-02-18T17:22:57Z","timestamp":1739899377000},"page":"4571-4584","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["TenGraph: A Tensor-Based Graph Query Engine"],"prefix":"10.14778","volume":"17","author":[{"given":"Guanghua","family":"Li","sequence":"first","affiliation":[{"name":"HKUST (Guangzhou), Guangzhou, China"}]},{"given":"Hao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Huawei Cloud Database, Innovation Lab, Beijing, China"}]},{"given":"Xibo","family":"Sun","sequence":"additional","affiliation":[{"name":"HKUST, Hong Kong, China"}]},{"given":"Qiong","family":"Luo","sequence":"additional","affiliation":[{"name":"HKUST and HKUST (Guangzhou), Guangzhou and Hong Kong, China"}]},{"given":"Yuanyuan","family":"Zhu","sequence":"additional","affiliation":[{"name":"Wuhan University, Wuhan, China"}]}],"member":"320","published-online":{"date-parts":[[2025,2,18]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"2018. 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