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Reconfigurable Technol. Syst."],"published-print":{"date-parts":[[2026,3,31]]},"abstract":"<jats:p>Field-Programmable Gate Arrays (FPGAs) are increasingly used in cloud platforms to accelerate diverse workloads, thanks to their reconfigurability and high performance. However, in multi-tenant cloud environments, existing FPGA virtualization mechanisms fail to align with dynamic application demands due to their static partitioning methods, leading to significant internal fragmentation.<\/jats:p>\n                  <jats:p>\n                    To address these issues, we present\n                    <jats:sc>Tetris<\/jats:sc>\n                    , an FPGA virtualization framework that supports flexible and dynamic reconfigurable resource allocation to improve cloud platform deployment efficiency. Specifically,\n                    <jats:sc>Tetris<\/jats:sc>\n                    deploys nested dynamic reconfigurable regions on FPGAs and adopts a tree structure to manage reconfigurable resources, enabling fine-grained resource reallocation at runtime. Enabled by the proposed fat-tree-based data transmission architecture between reconfigurable regions,\n                    <jats:sc>Tetris<\/jats:sc>\n                    can map dataflow-based applications onto these regions effectively. Additionally,\n                    <jats:sc>Tetris<\/jats:sc>\n                    offers dual-level resource optimization strategies to help system to balance the resource utilization and run-time compilation overhead.\n                  <\/jats:p>\n                  <jats:p>\n                    We evaluate\n                    <jats:sc>Tetris<\/jats:sc>\n                    with dataflow HLS benchmarks. Experimental results show that\n                    <jats:sc>Tetris<\/jats:sc>\n                    achieves a 1.16\u2009\n                    <jats:inline-formula content-type=\"math\/tex\">\n                      <jats:tex-math notation=\"LaTeX\" version=\"MathJax\">\\(\\times\\)<\/jats:tex-math>\n                    <\/jats:inline-formula>\n                    improvement in resource utilization compared to advanced FPGA virtualization frameworks and delivers a 1.3\u2009\n                    <jats:inline-formula content-type=\"math\/tex\">\n                      <jats:tex-math notation=\"LaTeX\" version=\"MathJax\">\\(\\times\\)<\/jats:tex-math>\n                    <\/jats:inline-formula>\n                    increase in run-time throughput, incurring less than 30% additional compilation latency.\n                    <jats:sc>Tetris<\/jats:sc>\n                    enables scalable, on-demand cloud FPGA acceleration, improving adaptability across different workloads.\n                  <\/jats:p>","DOI":"10.1145\/3779447","type":"journal-article","created":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T14:38:35Z","timestamp":1765377515000},"page":"1-32","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["TETRIS: A Novel FPGA Virtualization Framework for Fine-grained Sharing via Hierarchical Reconfiguration"],"prefix":"10.1145","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-0353-8132","authenticated-orcid":false,"given":"Wenbin","family":"Teng","sequence":"first","affiliation":[{"name":"University of Science and Technology of China, Hefei, China and Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2240-6672","authenticated-orcid":false,"given":"Wenqi","family":"Lou","sequence":"additional","affiliation":[{"name":"Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7281-1203","authenticated-orcid":false,"given":"Teng","family":"Wang","sequence":"additional","affiliation":[{"name":"Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8391-5526","authenticated-orcid":false,"given":"Lei","family":"Gong","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China and Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8453-0495","authenticated-orcid":false,"given":"Chao","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China and Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8360-3143","authenticated-orcid":false,"given":"Xuehai","family":"Zhou","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China and Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2026,3,6]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/HOTI.2017.13"},{"key":"e_1_3_1_3_2","unstructured":"Alibaba. 2020. 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