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With the help of the computing power, it can be even distributed to many computing nodes in the cluster, thus realizing the huge computation ability about large data.
Allocating too many computing nodes can lead to high execution time.
Our approach in implementing L-BFGS over the HPCC Systems platform distributes the parameter vector over many computing nodes.
A data sparsity measure is used to divide the data before distributing the columns in the network over many computing nodes based on the MapReduce framework.
We demonstrate SeqPig's scalability over many computing nodes and illustrate its use with example scripts.
However, it is necessary to pay for as many computing nodes as needed, which are charged at an hourly rate.
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The proposed tomographic reconstruction engine can efficiently process large-scale tomographic data using many compute nodes and minimize reconstruction times.
In our work, we consider easing the implementation and parallelization of different reconstruction algorithms using a MapReduce-like middleware [6, 12, 13], and scale reconstruction operations to many compute nodes.
To date, NGS-applications using MPI to spread the load over many compute nodes rather than just on many threads, have been scarce.
Designing an efficient scheduling strategy for minimizing the total processing time of loads is challenging since it has to consider many intrinsic characteristics of the system such as the availability and heterogeneity of computing nodes, network topology and capacity.
The swept rule decomposes space and time among computing nodes in ways that exploit the domains of influence and the domain of dependency, making it possible to communicate once per many timesteps without redundant computation.
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