Nevertheless, large-scale problems often require parallel computation on supercomputers or clusters of small computers that share the work.
The algorithm is advantageous in comparison with other pose estimation algorithms including those based on classical filter approaches because of the small computation time.
Now, when compared to Mowgli, the rearrangements tried by MowgliNNI n on weak edges to obtain a better gene tree are done at the price of a relatively small computation time overcost.
Essentially, the Four Russians technique enumerates solutions for small computations, stores these solutions in lookup tables, and then accelerates bigger computations by replacing the execution of sub-computations with queries to the lookup tables.
In this paper, we propose a load balancing strategy that has the following features: (1) estimating the potential load of real gateways with small computation time and no communication overhead, (2) asynchronous alarm sent when the utilization of a real gateway exceeds a critical threshold, and (3) WAP-awareness.
Every part of the source code contains a small computation that consumes a little time, a characteristic called a flat profile.
It leads to a high-performance simulation, combining accuracy (global simulation error less than 1 dBW) and small computation time (gain of about 10,000 times compared to a full deterministic reference model).
In other words, BP is a way of organizing the global computation of marginal beliefs in terms of smaller local computations.
The belief propagation (BP) algorithm, proposed by Pearl [1], is a way of organizing the global computation of marginal beliefs in terms of smaller local computations within the graph.
Since GP iteratively partitions a large (G_v) into a series of small graphs, whose computations are independent, the computation on a vertex can be easily parallelized.
