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Consequently, if the interface is not homogeneously distributed throughout the domain, standard domain decomposition (DD) strategies lead to imbalanced workload distributions.
These conflicting requirements and goals are difficult to optimize due to the unknown runtime conditions, such as the availability of the resources and random workload distributions.
From a rare events perspective, scheduling disciplines that work well under light (exponential) tailed workload distributions do not perform well under heavy (power) tailed workload distributions, and vice versa, leading to fundamental problems in designing schedulers that are robust to distributional assumptions on the job sizes.
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The problem of finding efficient workload distribution techniques is becoming increasingly important today for heterogeneous distributed systems where the availability of compute nodes may change spontaneously over time.
Using the simulation system, simulations with real workload distribution are conducted.
A two-level partitioning is used for the workload distribution among computing devices of hybrid nodes.
Essentially, we develop two indexing algorithms to enable workload distribution and cluster-based filtering.
The unbalanced workload distribution and the huge communication overhead are two main obstacles for the heterogeneous cooperative computing.
As such, they present to the developers well known problems of synchronization, communication, workload distribution, and so on.
Furthermore, we derive the energy-optimal workload distribution and propose a runtime environment for Heavy/Light MCU platforms.
The suggestion in the book, of using index cards to represent family chores, then dividing them up to show the workload distribution, seems like it would help a lot of people.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com