computational requirement

USAGE SUMMARY

The phrase "computational requirement" is correct and usable in written English.
It can be used when discussing the necessary computational resources or conditions needed to perform a specific task or process in computing or data analysis. Example: "The computational requirement for this simulation is significantly higher than we initially anticipated, necessitating an upgrade to our hardware."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

Since the neural network is used to model the nonlinear dynamics only, not the overall process, a relatively small sized network is required, thus reducing computational requirement.

Chemical Engineering Science

Reducing ST greatly reduces the computational requirement making ESNs suitable even for tasks that require a high frequency of operation.

Neural Networks

Considering millions or more of bio-OMIC features for each sample, although the exhaustive search guarantees the detection of optimal feature subset, its computational requirement exceeds the capacity of any high-performance computing systems under the current parallel computing architecture.

BioMed Research International

Every new Twitter user and every new connection results in an exponentially greater computational requirement.

TechCrunch

Its computational requirement is one, which presents less computational complexity.

EURASIP Journal on Advances in Signal Processing

The computational requirement is high for this method.

EURASIP Journal on Advances in Signal Processing

The proposed schemes can decouple the compensation of the tresulttter and receiner IQ imbanance froverallcompensation of the channelowertraining

EURASIP Journal on Advances in Signal Processing

Specifically, decreasing alleviates the computational requirement at the expense of a reduced CFO acquisition range.

EURASIP Journal on Wireless Communications and Networking

However, it has vitally high computational requirement, especially with the increased number of associated objects.

EURASIP Journal on Advances in Signal Processing

On the other hand, SVD combined with transforms reduce the amount of computational requirement.

Complex & Intelligent Systems

The number of components has doubled and the computational requirement has grown by orders of magnitude.

Probability, Uncertainty and Quantitative Risk

Expert writing Tips

Best practice

When discussing performance, quantify the "computational requirement" with specific metrics like FLOPS (floating-point operations per second) or memory usage to provide concrete details.

Common error

Don't only consider the initial "computational requirement". Factor in how requirements will scale with increasing data volume or user load to avoid future bottlenecks.

Linguistic Context

The phrase "computational requirement" functions primarily as a noun phrase, often acting as the subject or object of a sentence. It describes the necessary computational resources for a specific task. Ludwig AI confirms its grammatical correctness.

Expression frequency: Very common

Frequent in

Science

90%

News & Media

5%

Formal & Business

5%

Less common in

Academia

0%

Encyclopedias

0%

Wiki

0%

Ludwig's WRAP-UP

The phrase "computational requirement" is a common and grammatically correct term, as verified by Ludwig AI, used to describe the computing resources necessary for a task. Predominantly found in scientific and technical contexts, its use emphasizes the need for specific processing power, memory, and algorithmic efficiency. When using the phrase, consider quantifying the requirements with metrics like FLOPS or memory usage. A key error to avoid is overlooking how the "computational requirement" will scale with increasing data, and one should consider alternatives such as "computing needs" or "processing demands". Its prevalent usage in authoritative sources underscores its importance in technical discourse.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

computing needs

Replaces 'requirement' with 'needs', focusing on what is necessary for computation.

computational load

Focuses on the amount of computation that needs to be performed.

processing demands

Emphasizes the demands placed on processing capabilities.

computational resources

Focuses on the available resources required for computation.

computing capacity

Highlights the capacity needed to fulfill the computation.

processing power needed

Specifies the power necessary for the computational task.

system requirements

Broader term including hardware, software, and computational aspects.

performance requirements

Broader term focusing on the performance needed from a computational system.

algorithmic complexity

Addresses the complexity of the algorithm and its impact on computation.

hardware specifications

Focuses on the hardware aspect necessary for the computation.

FAQs

How can I reduce the "computational requirement" of an algorithm?

You can reduce the "computational requirement" by optimizing the algorithm's code, using more efficient data structures, or employing parallel processing techniques. Also, consider approximation algorithms, which may sacrifice some accuracy for speed.

What does "computational requirement" mean in the context of machine learning?

In machine learning, "computational requirement" refers to the resources (time, memory, processing power) needed to train and run a model. High "computational requirement" might necessitate specialized hardware or cloud computing.

What's the difference between "computational requirement" and "computational complexity"?

"Computational requirement" refers to the actual resources needed to execute a task, while "computational complexity" is a theoretical measure of the resources (usually time and space) required by an algorithm as a function of the input size.

Which factors influence the "computational requirement" of a software application?

Factors that influence the "computational requirement" include the algorithm's efficiency, the size and type of data being processed, the programming language used, and the underlying hardware architecture.