{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T13:41:21Z","timestamp":1777902081735,"version":"3.51.4"},"reference-count":21,"publisher":"SAGE Publications","issue":"4-5","license":[{"start":{"date-parts":[[2004,5,1]],"date-time":"2004-05-01T00:00:00Z","timestamp":1083369600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["SIMULATION"],"published-print":{"date-parts":[[2004,5]]},"abstract":"<jats:p>The recent development of distributed processing platforms, such as clusters of workstations, makes the use of distributed applications more extensive. A fundamental issue affecting performance in distributed systems is the scheduling of tasks to processors. The problem of solving the scheduling of parallel programs modelled with a task precedence graph (TPG) has been extensively studied. Scheduling algorithms of TPGs can be solved by a one-step method when a fixed number of processors is considered or through a two-step method by first creating an unbounded number of groups of tasks (clusters) and subsequently assigning these clusters to a bounded number of processors. The goal of this work is to present a new mapping algorithm called TASC (Task ASsignment exploiting Concurrency) to solve this second step of assigning clusters to processors. The effectiveness of TASC is established through simulation for a set of synthetic graphs that model real applications.<\/jats:p>","DOI":"10.1177\/0037549704045444","type":"journal-article","created":{"date-parts":[[2004,9,13]],"date-time":"2004-09-13T20:00:29Z","timestamp":1095105629000},"page":"243-254","source":"Crossref","is-referenced-by-count":0,"title":["Modeling Clustered Task Graphs for Scheduling Large Parallel Programs in                 Distributed Systems"],"prefix":"10.1177","volume":"80","author":[{"given":"Concepci\u00f3","family":"Roig","sequence":"first","affiliation":[{"name":"Universitat de Lleida, Department of CS, Jaume II 69, 25001 Lleida,                         Spain,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ana","family":"Ripoll","sequence":"additional","affiliation":[{"name":"Universitat Aut\u00f2noma de Barcelona, Department of CS, 08193                         Barcelona, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emilio","family":"Luque","sequence":"additional","affiliation":[{"name":"Universitat Aut\u00f2noma de Barcelona, Department of CS, 08193                         Barcelona, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2004,5,1]]},"reference":[{"key":"atypb1","doi-asserted-by":"publisher","DOI":"10.1109\/71.888636"},{"key":"atypb2","volume-title":"Parallel program development for cluster computing","author":"Cunha, J. 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