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However, the large computational demand encumbers the deployment of MISR in practice. In this work, we propose a distributed optimization framework based on data parallelism for fast large-scale MISR using multi-GPU acceleration named FL-MISR. The scaled conjugate gradient (SCG) algorithm is applied to the distributed subfunctions and the local SCG variables are communicated to synchronize the convergence rate over multi-GPU systems towards a consistent convergence. Furthermore, an inner-outer border exchange scheme is performed to obviate the border effect between neighboring GPUs. The proposed FL-MISR is applied to the computed tomography (CT) system by super-resolving the projections acquired by subpixel detector shift. The SR reconstruction is performed on the fly during the CT acquisition such that no additional computation time is introduced. FL-MISR is extensively evaluated from different aspects and experimental results demonstrate that FL-MISR effectively improves the spatial resolution of CT systems in modulation transfer function (MTF) and visual perception. Comparing to a multi-core CPU implementation, FL-MISR achieves a more than 50<jats:inline-formula><jats:alternatives><jats:tex-math>$$\\times$$<\/jats:tex-math><mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:mo>\u00d7<\/mml:mo><\/mml:math><\/jats:alternatives><\/jats:inline-formula>speedup on an off-the-shelf 4-GPU system.<\/jats:p>","DOI":"10.1007\/s11554-021-01181-0","type":"journal-article","created":{"date-parts":[[2021,11,29]],"date-time":"2021-11-29T07:02:32Z","timestamp":1638169352000},"page":"331-344","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["FL-MISR: fast large-scale multi-image super-resolution for computed tomography based on multi-GPU acceleration"],"prefix":"10.1007","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9999-2542","authenticated-orcid":false,"given":"Kaicong","family":"Sun","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Trung-Hieu","family":"Tran","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jajnabalkya","family":"Guhathakurta","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sven","family":"Simon","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,11,29]]},"reference":[{"issue":"5","key":"1181_CR1","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1109\/MSP.2003.1203207","volume":"20","author":"S Park","year":"2003","unstructured":"Park, S., Park, M., Kang, M.G.: Super-resolution image reconstruction: a technical overview. 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