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Iterative computation Compute phase For each computing node, sequentially compute the maximal cliques of its assigned subgraphs by the GP or hybrid algorithm; Shuffle phase Evenly reshuffle all the intermediate subgraphs across the nodes; .
Note that TM′ < TM and TR′ < TR. iiHadoop accelerates the incremental iterative computation by executing iterations asynchronously (i.e., two iterations can concurrently process their data).
Incremental iterative computation means processing the changed data iteratively based on the previous computed results.
In this paper, an iterative computation guidance law (ICGL) is proposed to compute a series of state variables to get the solution of a control variable for a UAV conducting rendezvous with a tanker in AAR.
It is hence desirable to periodically refresh the iterative computation so that the new changes can be quickly reflected in the computed results.
However, in the proposed method, when either the maximum iteration count is exhausted or all candidate solutions acquire the same fitness, the iterative computation stops.
Spark depends on memory for fast iterative computation.
The The optimal θ is derived by the iterative computation.
It is based on iterative computation and the equations are derived.
In this paper, we analyze the reason why iterative computation sometimes does not converge.
The program of iterative computation consists of a series of MapReduce cycles.
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