Sentence examples for core cluster and from inspiring English sources

Using these instances, Amazon launched a 26,496 core cluster and evaluated it against the recent Top500 scores for supercomputers.

Note that if every element in ℳ has multiplicity 1 then every cluster is a core cluster and our algorithm works precisely like the greedy consensus method for phylogenetic trees [ 18].

Finally, the last step is responsible for the merge of core clusters and it is performed with a single MapReduce algorithm.

The clusters C in ℬ with (C) > 0 are then partitioned into core clusters and ambiguous clusters (Lines 13-17).

After including the outgroup 560 (13%) of 4,460 were core clusters and of these 363 were single copy.

Using this multiset a collection of 15 non-trivial clusters is derived from the input trees, of which 12 are core clusters and 3 are ambiguous clusters.

However, dispensable clusters and strain-specific clusters are still rich in transcription, replication, recombination and repair and cell wall/membrane/envelope biogenesis and cell motility, while the clusters' numbers of translation, ribosomal structure and biogenesis decrease sharply as compared to the core clusters and whole clusters.

Using this multiset and the default value of ⌈l/2⌉ = 3 for the threshold t we obtain the 4 non-trivial core clusters and the non-trivial ambiguous clusters { O, S} (two copies) and { I, O, S} (one copy) to build a consensus tree.

Furthermore, a hierarchical parallelization scheme is designed to map the MD algorithm to Godson-T many-core cluster and a simple performance model is derived, which suggests that the optimization scheme is likely to scale well toward exascale.

This speed makes it fairly feasible to genome-wide applications, as a single threading scan for a middle-size genome of 5000 genes takes <1 day on a 100-core cluster and that using multiple threading programs, such as LOMETS, should take <1 week.

The results show CloudBurst scales very well as the number of cores increases: the 96-core cluster was 3.5 times faster than the 24-core cluster and reduced the running time of the serial RMAP execution from >14 h to ∼8 min (>100× speedup).