The phrase "amount of data being processed" is correct and usable in written English.
It can be used when discussing the quantity or volume of data that is currently being handled or analyzed in a particular context, such as computing or data analysis.
Example: "The system is struggling to keep up with the amount of data being processed during peak hours."
Alternatives: "volume of data being handled" or "quantity of data being analyzed".
The main purpose of this phase is to significantly reduce the amount of data being processed in the production scheduling progress.
The CPU adopts itself dynamically to the amount of data being processed, resulting in energy savings of up to 30% when compared to the power consumed at normal times.
Due to the heuristic approach, the execution speed of BLAST is significantly increased but the amount of data being processed is very large and is increasing at an exponential rate; such as UniMES for metagenomic data sets [4], which continues to expand exponentially as next generation sequencing (NGS).
This huge amount of data is processed on more than 140 computing centers distributed across 34 countries.
Intel frequently focuses on popular brand names in its post -- implying that even larger amounts of data are processed in an "Internet minute" if you factor in the companies' competitors.
The potential Achilles heel of any automated process is the need to balance minimizing human intervention against ensuring data quality, a trade-off that becomes increasingly relevant as ever larger amounts of data are processed.
A large amount of Facebook data was processed with psycholinguistic methods to detect emotional contagion, by using weather as an instrumental variable [62].
Because of their high peak performance and energy efficiency, massively parallel accelerators such as graphics processing units (GPUs) are quickly spreading in high-performance computing, where large amounts of floating-point data are processed, transferred, and stored.
Volume refers to the amount of data being stored and processed.
The latter is particularly beneficiarry for many BigData problems, where a large amount of data is repetetively processed through the use of relatively simple operations.
The latter is beneficiary for many Big Data problems, where a large amount of data is continuously processed through the use of relatively simple operations.
