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In global adaptivity, it is very often the case that there exists only a particular region of interest on the macro scale, which leads to only micro simulations in that region to be active. From a performance perspective this is highly inefficient, because it means that some processors solve a large number of micro simulations, while other processors are idle. In a recent study where we scaled the two-scale-heat-conduction case to have 128 micro simulations, we saw the effect of the load imbalance:
A dynamic load balancing technique which would redistribute the micro simulations across processors would aide to increased performance and scalability.
The text was updated successfully, but these errors were encountered:
In global adaptivity, it is very often the case that there exists only a particular region of interest on the macro scale, which leads to only micro simulations in that region to be active. From a performance perspective this is highly inefficient, because it means that some processors solve a large number of micro simulations, while other processors are idle. In a recent study where we scaled the two-scale-heat-conduction case to have 128 micro simulations, we saw the effect of the load imbalance:
A dynamic load balancing technique which would redistribute the micro simulations across processors would aide to increased performance and scalability.
The text was updated successfully, but these errors were encountered: