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The main processes can be highly parallelized with no need to assemble the global stiffness matrix.
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Current adaptive mesh refinement (AMR) simulations require algorithms that are highly parallelized and manage memory efficiently.
Unlike Central Processing Units (CPUs), GPUs are highly parallelized, which makes it suitable for accelerating scientific computing algorithms like SPH.
Even though the retrieval and extraction process is highly parallelized, generating siblings can take up to 9 s.
Graphics Processing Units (GPUs) are highly parallel programmable coprocessors that provide massive computation when the needed operations are properly parallelized.
While this can become an issue, it is easily handled as the MCS algorithm is highly parallel and, in the case of long running simulation requirements, may be easily parallelized in order to quickly simulate complex systems.
Graphics Processing Units (GPUs) are highly parallel programmable co-processors that provide massive computation when the needed operations are properly parallelized.
RNA-seq is a highly parallelized sequencing technology that allows for comprehensive transcriptome characterization and quantification (Wang et al., 2009).
We have also illustrated how a valuable legacy code in the biosciences can be effectively parallelized with minimal code changes.
These programs can be easily parallelized with multi-threading, but they usually require large memory to build an index for the human genome.
Furthermore, the implemented methods are fully parallelized with parallel efficiency of 80 90% on the problems tested.
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CEO of Professional Science Editing for Scientists @ prosciediting.com