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Modeling 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 artikel
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 ofTASC is established through simulation for a set of synthetic graphs that model real applications.
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