{"id":1183,"date":"2025-01-10T15:50:39","date_gmt":"2025-01-10T15:50:39","guid":{"rendered":"http:\/\/localhost:8000\/?page_id=1183"},"modified":"2026-04-16T17:32:41","modified_gmt":"2026-04-16T14:32:41","slug":"home","status":"publish","type":"page","link":"https:\/\/harsh-project.eu\/en\/","title":{"rendered":"\u0391\u03c1\u03c7\u03b9\u03ba\u03ae"},"content":{"rendered":"
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HAR.S.H. Project<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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SIMILARITY SEARCH IN LARGE-SCALE TIME SERIES COLLECTIONS WITH\nHARDWARE AWARENESS \/ HARDWARE-AWARE EXTREME SCALE\nSIMILARITY SEARCH<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\n\t\t\t\t\t\t\t\t\tDesigned by Freepik<\/a>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The Project<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\tHAR.S.H aims to address major challenges in the large-scale processing of time series collections derived from real-world applications. Large-scale time series data collections are now present in nearly every scientific and societal domain. HAR.S.H will design and implement an extensive suite of algorithms, data structures, and mechanisms to tackle the scalability problem in analyzing vast volumes of time series data, leveraging modern and emerging hardware technologies. The algorithms, data structures, and mechanisms developed will form a robust library, ensuring their easy and efficient use across a wide range of applications. Specifically, HAR.S.H aims to:\n\n\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\n\t\t\t\t\t\tDesign and develop a new generation of algorithms and data structures that enable efficient parallel and distributed similarity search on large time series collections.\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\n\t\t\t\t\t\tLeverage modern hardware technologies by studying their impact on the performance and scalability of such software.\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\n\t\t\t\t\t\tEnable analysis of multimodal data\u2014including text, images, and video\u2014through integrations using deep learning models.\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t

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Latest News<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tSchool on the Practice and Theory of Distributed Computing\t\t\t\t\t\t<\/a>\n\t\t\t\t\t<\/h5>\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t

\n\t\t\t\t\t\tExcited to announce SPTDC 2026! Organized by HAR.S.H., this year\u2019s school brings together experts from academia and industry to explore the future of Distributed Computing.\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tPresentation of HAR.S.H to High Schools Visits\t\t\t\t\t\t<\/a>\n\t\t\t\t\t<\/h5>\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t

\n\t\t\t\t\t\tPresenting our research work to high school students during their visits to the Department of Computer Science, at the Uniersity of Crete.\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tPaper Presented at PPoPP 2026\t\t\t\t\t\t<\/a>\n\t\t\t\t\t<\/h5>\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t

\n\t\t\t\t\t\tConcurrent Balanced Augmented Trees\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\n\t\t\t\t\t\tSharded Elimination and Combining for Highly-Efficient Concurrent Stacks\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Similarity Search in Large-Scale Time Series Collections with Hardware Awareness<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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HARSH: Hardware-Aware extReme-scale Similarity search<\/strong><\/p>

  • Project Code:<\/strong> \u03a5\u03a03\u03a4\u0391-0560901<\/li>
  • Project Start Date:<\/strong> April 15, 2025<\/li>
  • Project End Date:<\/strong> June 30, 2026<\/li>
  • Funding Body:<\/strong> Ministry of Education, Religious Affairs and Sports,\nGreece 2.0, National Recovery and Resilience Plan<\/li>
  • Host Institution:<\/strong> University of Crete (UoC), Department of Computer Science<\/li><\/ul>

    The project is implemented under the National Recovery and Resilience plan \"Greece 2.0\"
    with funding from the European Union \u2013 NextGenerationEU<\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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    HAR.S.H. Project \u0391\u039d\u0391\u0396\u0397\u03a4\u0397\u03a3\u0397 \u039f\u039c\u039f\u0399O\u03a4\u0397\u03a4\u0391\u03a3 \u03a3\u0395 \u039c\u0395\u0393\u0391\u039b\u0395\u03a3 \u03a3\u03a5\u039b\u039b\u039f\u0393\u0395\u03a3 \u03a3\u0395\u0399\u03a1\u03a9\u039d \u0394\u0395\u0394\u039f\u039c\u0395\u039d\u03a9\u039d \u03a3\u03a5\u039d\u03a5\u03a0\u039f\u039b\u039f\u0393\u0399\u0396\u039f\u039d\u03a4\u0391\u03a3 \u03a4\u039f Y\u039b\u0399\u039a\u039f \/ HARDWARE-AWARE EXTREME SCALE SIMILARITY SEARCH \u03a0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03b1 Designed by Freepik \u03a4\u03bf \u0388\u03c1\u03b3\u03bf \u03a4\u03bf HARSH \u03c3\u03c4\u03bf\u03c7\u03b5\u03cd\u03b5\u03b9 \u03c3\u03c4\u03b7\u03bd \u03b1\u03bd\u03c4\u03b9\u03bc\u03b5\u03c4\u03ce\u03c0\u03b9\u03c3\u03b7 \u03c3\u03b7\u03bc\u03b1\u03bd\u03c4\u03b9\u03ba\u03ce\u03bd \u03c0\u03c1\u03bf\u03ba\u03bb\u03ae\u03c3\u03b5\u03c9\u03bd \u03c3\u03c4\u03b7\u03bd \u03b5\u03c0\u03b5\u03be\u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1 \u03bc\u03b5\u03b3\u03ac\u03bb\u03b7\u03c2 \u03ba\u03bb\u03af\u03bc\u03b1\u03ba\u03b1\u03c2 \u03c3\u03c5\u03bb\u03bb\u03bf\u03b3\u03ce\u03bd \u03c3\u03b5\u03b9\u03c1\u03ce\u03bd \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u03c0\u03bf\u03c5 \u03c0\u03c1\u03bf\u03ba\u03cd\u03c0\u03c4\u03bf\u03c5\u03bd \u03b1\u03c0\u03cc \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ad\u03c2 \u03b5\u03c6\u03b1\u03c1\u03bc\u03bf\u03b3\u03ad\u03c2. \u039f\u03b9 \u03c3\u03c5\u03bb\u03bb\u03bf\u03b3\u03ad\u03c2 \u03c3\u03b5\u03b9\u03c1\u03ce\u03bd \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u03bc\u03b5\u03b3\u03ac\u03bb\u03b7\u03c2 \u03ba\u03bb\u03af\u03bc\u03b1\u03ba\u03b1\u03c2 \u03c3\u03c5\u03bd\u03b1\u03bd\u03c4\u03ce\u03bd\u03c4\u03b1\u03b9 \u03c0\u03bb\u03ad\u03bf\u03bd \u03c3\u03c7\u03b5\u03b4\u03cc\u03bd \u03c3\u03b5 \u03ba\u03ac\u03b8\u03b5 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[…]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"open","template":"","meta":{"site-sidebar-layout":"no-sidebar","site-content-layout":"page-builder","ast-site-content-layout":"full-width-container","site-content-style":"unboxed","site-sidebar-style":"unboxed","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"disabled","ast-breadcrumbs-content":"","ast-featured-img":"disabled","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"enabled","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center 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