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However, conventional TC algorithms based on binary matrix operations suffer from low computational efficiency due to high storage\u2010to\u2010computation ratios and irregular memory access patterns, both exacerbated by the bandwidth bottleneck of the von Neumann architecture. To overcome these limitations, this paper presents a binary vector\u2010matrix multiplication circuit based on in\u2010memory computing, specifically designed to accelerate TC algorithms. The intersection\u2010based TC approach is first reformulated as a constrained binary matrix multiplication problem, enabling the design of a programmable in\u2010memory computing circuit. By modulating the gate voltage of CMOS transistors, the circuit efficiently manages constraints to accelerate vector\u2010matrix operations. Building on this foundation, a hardware acceleration scheme leveraging block partitioning and parallel computing is proposed. PSPICE simulation results demonstrate an average computational accuracy exceeding 99% across various matrix sizes and robustness against noise, maintaining over 95% accuracy under 10% voltage variation. Compared to traditional digital processors, the proposed solution achieves a speedup of approximately three orders of magnitude (1000\n).<\/jats:p>","DOI":"10.1002\/cta.70057","type":"journal-article","created":{"date-parts":[[2025,7,8]],"date-time":"2025-07-08T03:35:06Z","timestamp":1751945706000},"page":"1350-1362","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["In\u2010Memory Binary Vector\u2010Matrix Multiplication Circuit Design for Triangle Counting Algorithm Acceleration"],"prefix":"10.1002","volume":"54","author":[{"given":"Sichun","family":"Du","sequence":"first","affiliation":[{"name":"The College of Computer Science and Electronic Engineering Hunan University  Changsha China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-1001-2037","authenticated-orcid":false,"given":"Yu","family":"Dong","sequence":"additional","affiliation":[{"name":"The College of Computer Science and Electronic Engineering Hunan University  Changsha China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Li","sequence":"additional","affiliation":[{"name":"The College of Computer Science and Electronic Engineering Hunan University  Changsha China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3929-9930","authenticated-orcid":false,"given":"Chen","family":"Sun","sequence":"additional","affiliation":[{"name":"The College of Computer Science and Electronic Engineering Hunan University  Changsha China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pingdan","family":"Xiao","sequence":"additional","affiliation":[{"name":"The College of Computer Science and Electronic Engineering Hunan University  Changsha China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qinghui","family":"Hong","sequence":"additional","affiliation":[{"name":"The College of Computer Science and Electronic Engineering Hunan University  Changsha China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,7,8]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2815554"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/2775108"},{"key":"e_1_2_8_4_1","doi-asserted-by":"crossref","unstructured":"L.Becchetti P.Boldi C.Castillo andA.Gionis \u201cEfficient Semi\u2010Streaming Algorithms for Local Triangle Counting in Massive Graphs \u201d inProceedings of the 14th ACM Sigkdd International Conference on Knowledge Discovery and Data Mining KDD '08 (Association for Computing Machinery 2008):16\u201324 https:\/\/doi.org\/10.1145\/1401890.1401898.","DOI":"10.1145\/1401890.1401898"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3375392"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/1839490.1839494"},{"key":"e_1_2_8_7_1","doi-asserted-by":"crossref","unstructured":"W. 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