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ArtikelModeling Clustered Task Graphs For Scheduling Large Parallel Programs In Distributed Systems  
Oleh: Roig, Concepció ; Ripoll, Ana ; Luque, Emilio
Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Simulation vol. 80 no. 4-5 (Apr. 2004), page 243-254.
Topik: Static mapping; modelling parallel programs; scheduling algorithms; cluster-mapping heuristics; message-passing computation model
Fulltext: 243.pdf (467.54KB)
Isi artikelThe 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 ofTASC is established through simulation for a set of synthetic graphs that model real applications.
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