Price: $50.99
(as of Nov 23,2024 14:06:43 UTC – Details)

ASIN ‏ : ‎ B09GW2Q4N1
Publisher ‏ : ‎ The MIT Press (August 2, 2022)
Publication date ‏ : ‎ August 2, 2022
Language ‏ : ‎ English
File size ‏ : ‎ 24319 KB
Text-to-Speech ‏ : ‎ Enabled
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 265 pages
Page numbers source ISBN ‏ : ‎ 0262046857

High-Performance Big Data Computing for Scientific and Engineering Computation

In today’s data-driven world, the ability to process and analyze vast amounts of data is crucial for scientific and engineering advancements. High-performance computing (HPC) techniques are essential for handling big data in fields such as genomics, climate modeling, and computational fluid dynamics.

Big data computing involves the use of powerful computing systems and algorithms to process and analyze massive datasets. This requires specialized hardware, software, and expertise to ensure efficient and accurate results. HPC systems, such as supercomputers, are commonly used for these tasks due to their high processing power and parallel computing capabilities.

In scientific and engineering computation, big data computing plays a vital role in tasks such as simulation, modeling, and data analysis. For example, researchers can use HPC techniques to analyze large-scale genomic data to understand genetic variations and their impact on diseases. Engineers can also use big data computing to simulate complex fluid dynamics scenarios to optimize designs for aircraft or automobiles.

Overall, high-performance big data computing is essential for pushing the boundaries of scientific and engineering research. By harnessing the power of advanced computing technologies, researchers and engineers can unlock new insights and drive innovation in their respective fields.
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