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parallel processing

parallel processing

1 4.3
Using two or more processors at the same time to do work faster
  • noun
  • /ˈpærəˌlɛl ˈprɑːsɛsɪŋ/
  • Specialized
translation icon : procesamiento paralelo
  • In summary, visual perceptual mechanisms are presently characterized by two physiologically based parallel processing streams, each mediating different yet well-defined physical attributes of visual scenes.

And that's the most efficient way of doing parallel processing.

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Examples

  • Microprocessor farms, having replaced mainframe computers for offline analyses, allow parallel processing of events that keep up with the data flood.

    Academic text (2012)
  • A popular approach to the study of parallel processing in vision is based on the notion of local and global processing.

    Academic text (1997)
  • So you will understand not just cell programming, but in parallel programming and parallel processing, what the world is like beyond that.

  • Because of increased workloads, parallel processing may have caused additional work-related stress for those involved.

    Academic text (1990)
  • The efficiency and effectiveness of the parallel processing are largely dependent on the problems to be solved with selected algorithms and hardware architectures.

    Academic text (2001)
  • Splitting up the problem to be solved across multiple computer processors—parallel processing—can also cut solution time, the two said.

    Academic text (2007)
  • Modern video games often rely on parallel processing to increase frame rates and enhance graphics performance.

  • Using parallel processing, the researchers were able to analyze large datasets much more efficiently.

  • The software was designed for parallel processing, allowing it to execute multiple tasks simultaneously without lag.

Synonyms

parallelism
vsparallel processing
  • Specialized
1 7.1

Using several processors at the same time to make a computer work faster

focuses on using several processors to make tasks finish faster
parallelization
vsparallel processing
  • Specialized
1 7.8

Dividing a task into parts that run at the same time

is about using multiple processors at once rather than splitting work
concurrent operation
vsparallel processing
  • Specialized
1 5.6

Two or more actions that happen at the same time

is about using processors together at once to make tasks finish faster
multiprocessing
vsparallel processing
  • Specialized
4.4

To run computer tasks on more than one processor at the same time

is about using processors together broadly to increase task speed
parallel operation
vsparallel processing
  • Specialized
4.9

Doing more than one task at the same time on computers or machines

is about using processors together specifically to speed task execution
coprocessing
vsparallel processing
  • Specialized
6.3

Using more than one computer or machine to do tasks faster

is about multiple processors working together rather than adding auxiliary systems
concurrent execution
vsparallel processing
  • Specialized
6.7

Two or more programs run at the same time on one computer

emphasizes using more than one processor simultaneously to speed processing
simultaneous operation
vsparallel processing
4.4

Two or more things working at the same time

is focused specifically on using processors together to speed up computing tasks

How Parallel

parallel processing
  • Specialized
1 4.3
multiprocessing
  • Specialized
4.4
serial processing
  • Specialized
6.0

Surface Forms

Morphology

parallel + processing

The meaning is directly compositional: 'parallel' (occurring at the same time or alongside) plus 'processing' (carrying out operations) yields the idea of processing tasks simultaneously. This is a transparent, technical compound mirrored across languages and standard terminology, so a B1 learner who knows both words would likely infer the meaning.

Etymology

Parallel processing comes from a simple picture: many workers standing 'side by side' and each doing part of a job at the same time. So parallel means 'side by side' and processing means 'working on the task', and the phrase now means using several processors together to finish work faster.