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28.
11.
2014
Dynamic Load Balancing of High Performance Computing Applications
Matthias Lieber
TU Dresden
Load balance is crucial for an efficient usage of high performance
computers (HPC). Unbalanced workload of parallel processes leads to
waiting time at synchronization points and thus to waste of computing
resources. Many HPC simulation applications are based on partial
differential equations that are discretized in space and time to allow
the approximate numerical solution of the problem (e.g. weather forecast,
crash test simulations, computational fluid dynamics). The problem is
partitioned among the space dimensions for parallelization and integrated
forward into time, with periodic communication between the processes. The
partitioning influences the load balance among the processes as well as
the communication costs. If the workloads vary in space and time, a
balanced static partitioning is not possible and dynamic load balancing
methods need to be applied. The perfect solution is an NP-complete
problem, which additionally needs to be solved as fast as possible, so
heuristics with different trade-offs are used in practice. In this talk,
I will give an overview of the dynamic load balancing problem in general
and discuss various methods that have been developed, like graph-based
methods and space-filling curves. Additionally, I will talk about my own
experiences in dynamic load balancing a complex weather model and the
challenges to reach scalability up to 256ki cores.
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