Exploiting Knowledge of Temporal Behaviour in Parallel Programs for Improving Distributed Mapping
Issue date
2000Suggested citation
Roig Mateu, Concepció;
Ripoll, A.;
Senar, M.A.;
Guirado Fernández, Fernando;
Luque, Emilio;
.
(2000)
.
Exploiting Knowledge of Temporal Behaviour in Parallel Programs for Improving Distributed Mapping.
Lecture Notes in Computer Science, 2000, vol.1900, p. 262-271.
https://doi.org/10.1007%2F3-540-44520-X_35.
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Show full item recordAbstract
In the distributed processing area, mapping and scheduling
are very important issues in order to exploit the gain from parallelization.
The generation of efficient static mapping techniques implies a previous
modelling phase of the parallel application as a task graph, which
properly reflects its temporal behaviour. In this paper we use a new
model, the Temporal Task Interaction Graph (TTIG), which explicitly
captures the temporal behaviour of program tasks; and we evaluate the
advantages that derive from the use of the TTIG model in task allocation.
Experimentation was performed in a current PVM environment,
for a set of synthetic graphs which exhibit different ratios of computation/
communication cost (coarse-grain, medium-grain). The execution
times when these programs were mapped using the information contained
in the TTIG model, were compared with the times obtained using the
two following mapping alternatives: (a) PVM default scheme and, (b)
mapping strategy based on the classical model TIG (Task Interaction
Graph). The results confirm that with the TTIG model, better assignments
are obtained, providing improvements of up to 49% compared with
the PVM assignments and up to 30% compared with TIG assignments.