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pro vyhledávání: '"Michael Rilee"'
Parallelization is the only means by which it is possible to process large amounts of diverse data on reasonably short time scales. However, while parallelization is necessary for performant and scalable BigData analysis, it is insufficient. We obser
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a456427022acb671880730e66372356d
https://doi.org/10.5194/egusphere-egu23-16795
https://doi.org/10.5194/egusphere-egu23-16795
Autor:
Michael Rilee, Kwo-Sen Kuo
The real world does not live on a regular grid. The observations with the best spatiotemporal resolution are generally irregularly distributed over space and time, even though as data they are generally stored in arrays in files. Storing the diverse
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8d87251288dcf8c474c2568698fcd298
https://doi.org/10.5194/egusphere-egu22-10799
https://doi.org/10.5194/egusphere-egu22-10799
Autor:
Michael Rilee, Kwo-Sen Kuo
The only effective strategy to address the volume challenge of Big Data is “parallel processing”, e.g. employing a cluster of computers (nodes), in which a large volume of data is partitioned and distributed to the cluster nodes. Each of the clus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2ae91903c1035ca9a48b5795717c0866
https://doi.org/10.5194/egusphere-egu2020-20339
https://doi.org/10.5194/egusphere-egu2020-20339
Publikováno v:
Geophysical Research Abstracts; 2018, Vol. 20, p2402-2402, 1p
