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Batch systems face issues with workloads comprising millions of tasks with short runtimes—scheduling is most efficient for long-running jobs. In addition, the nature of heterogeneous computing systems makes task bundling impractical. Building on HTCondor, the Event Workflow Management System (EWMS) provides an efficient solution to thrive with both paradigms, while featuring user-friendly and self-healing principles. Here, we describe this method, its implementation, and a real-world application.more » « lessFree, publicly-accessible full text available July 18, 2026
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Ide, Nancy; Suderman, Keith; Tu, Jingxuan; Verhagen, Marc; Peters, Shanan E.; Ross, Ian; Lawson, Jon; Borg, Andrew; Pustejovsky, James (, LREC proceedings)Calzolari, Nicoletta; Bechet, Frederic; Blache, Philippe; Choukri, Khalid; Cieri, Christopher; Declerck, Thierry; Goggi, Thierry; Isahara, Hitoshi; Maegaard, Bente; Mariani, Joseph (Ed.)This paper provides an overview of the xDD/LAPPS Grid framework and provides results of evaluating the AskMe retrieval engine using datasets included in the BEIR benchmark. Our primary goal is to determine a solid baseline of performance to guide further development of our retrieval capabilities. Beyond this, we aim to dig deeper to determine when and why certain approaches perform well (or badly) on both in-domain and out-of-domain data, an issue that has to date received relatively little attention.more » « less
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Grasham, Catherine Fallon; Calow, Roger; Casey, Vincent; Charles, Katrina J.; de Wit, Sara; Dyer, Ellen; Fullwood-Thomas, Jess; Hirons, Mark; Hope, Robert; Hoque, Sonia Ferdous; et al (, npj Clean Water)
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