Publications | Scalable Computing & Cloud Laboratory

@InProceedings{PDP2016,
      AUTHOR = {Cicirelli, Franco and Forestiero, Agostino and Giordano, Andrea and Mastroianni, Carlo and Spezzano, Giandomenico},
      TITLE = {Parallel execution of space-aware applications in a Cloud environment},
      YEAR = {2016},
      MONTH = {February},
      BOOKTITLE = {24th Euromicro International Conference on Parallel, Distributed and Network-Based Computing (PDP 2016)},
      PAGES = {686-693},
      ADDRESS = {Heraklion, Crete, Greece},
      URL = {http://dx.doi.org/10.1109/PDP.2016.63},
      ABSTRACT = {This paper analyzes and evaluates the strategies and
implications related to the execution of parallel algorithms on a
distributed Cloud infrastructure, with the focus on an important
class of applications for which the execution is performed on
spatial data, dislocated on a bidimensional territory. Applications
of interest cover a wide spectrum ranging from Internet of Things
to social sciences, geology, swarm-inspired computation etc. The
territory is partitioned into regions, and regions are assigned to
parallel computational nodes to speed up the execution. Parallel
nodes are aligned through the exchange of messages in order to
ensure a coherent and efficient execution. The paper offers an
analysis of the parallelization cost in this context, especially in
terms of communication overhead, which is essential to estimate
the impact of porting the computation onto a Cloud environment.
More in particular, the paper evaluates two different strategies
for space partitioning, i.e., linear partitioning and bidimensional
partitioning, with a specific focus on scalability analysis, and
compares the two strategies when both options are exploitable.}
}