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Section: New Results
Efficient algorithmic for load balancing and code coupling in complex simulations
Dynamic load balancing for massively parallel coupled codes
In the field of scientific computing, load balancing is a major issue
that determines the performance of parallel applications. Nowadays,
simulations of real-life problems are becoming more and more complex,
involving numerous coupled codes, representing different models. In
this context, reaching high performance can be a great challenge. In
the PhD of Maria Predari (started in october 2013), we develop new
graph partitioning techniques, called co-partitioning, that address
the problem of load balancing for two coupled codes: the key idea is
to perform a coupling-aware partitioning, instead of
partitioning these codes independently, as it is usually
done. However, our co-partitioning technique requires to use graph
partitioning with fixed vertices, that raises serious issues
with state-of-the-art software, that are classically based on the
well-known recursive bisection paradigm (RB).
Indeed, the RB method often fails to produce partitions of good
quality. To overcome this issue, we propose a new direct