computational costs

USAGE SUMMARY

The phrase "computational costs" is correct and usable in written English.
It can be used when discussing the resources, such as time and processing power, required to perform computations or run algorithms. Example: "When developing new algorithms, it is essential to consider the computational costs to ensure efficiency and scalability."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

The gap in computation time, hence the computational costs, were increased for higher marker density.

Genetics, Selection, Evolution

However, computing several engine cycles results in excessive computational costs.

Computers & Fluids

But this increases the computational costs extensively.

Journal of Computational Physics

Table 1 Cryptographic operations and computational costs.

EURASIP Journal on Wireless Communications and Networking

Hence effectively, the computational costs involved is.

EURASIP Journal on Advances in Signal Processing

However its application involves large computational costs.

Mechanics of Advanced Materials and Modern Processes

Required iterations and computational costs are decreased.

Annals of Nuclear Energy

Furthermore, numerical studies are performed to reduce computational costs.

International Journal of Solids and Structures

Overall, the GDQM decreases the time and computational costs.

Composites Part B: Engineering

Conservation properties, accuracy and computational costs are monitored.

Journal of Computational Physics

Section 5 shows evaluation results on quality and computational costs.

EURASIP Journal on Advances in Signal Processing

Expert writing Tips

Best practice

When discussing different algorithms or methods, always quantify the "computational costs" using metrics like time complexity (Big O notation) or actual execution time to provide a clear comparison.

Common error

When evaluating "computational costs", don't only focus on CPU time. Memory usage, disk I/O, and network bandwidth can also significantly contribute to the overall cost, especially for large datasets or complex simulations.

Linguistic Context

The phrase "computational costs" functions as a noun phrase, typically serving as the subject or object of a sentence. It refers to the resources, such as time, memory, and energy, required to perform a computation. As Ludwig AI confirms, this is a correct and usable phrase in English.

Expression frequency: Very common

Frequent in

Science

95%

Formal & Business

3%

News & Media

2%

Less common in

Academia

0%

Encyclopedias

0%

Wiki

0%

Ludwig's WRAP-UP

In summary, "computational costs" is a noun phrase widely used to describe the resources needed to perform computations. Ludwig AI confirms its correctness and usability. It's most prevalent in scientific and technical contexts, serving the purpose of evaluating and comparing computational efficiency. When using the phrase, consider quantifying the costs with specific metrics like time complexity or execution time. A key takeaway is to not only focus on CPU time but also on memory usage and other resource constraints. While alternatives like "calculation expenses" and "processing expenses" exist, "computational costs" is a precise and frequently used term in its field. The abundance of examples confirms that this phrase is a staple in the scientific literature.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

calculation expenses

Focuses on the monetary aspect of the computation, similar to costs but emphasizing the financial outlay.

processing expenses

Similar to "computational costs" but highlights the expense associated with processing data or information.

computing resource consumption

Emphasizes the consumption of resources, such as memory and processing power, during computation.

algorithmic complexity

Refers to the amount of resources (time, memory) required by an algorithm, often expressed using Big O notation.

execution overhead

Focuses on the additional resources required to execute a program beyond the core computation.

operational expenses

Broadly relates to the expenses incurred during the operation of a computational process.

system resource utilization

Emphasizes how system resources are being used during computational tasks.

performance footprint

Focuses on the impact of computation on system performance, including memory and CPU usage.

resource intensity

Describes how intensively resources are used during a computational process.

processing load

Refers to the amount of processing required, impacting overall costs.

FAQs

What are some metrics to quantify "computational costs"?

Common metrics include execution time, memory usage, disk I/O, network bandwidth, and energy consumption. Time complexity (Big O notation) is also frequently used to express how the resources grow with input size.

How can I reduce "computational costs" in my algorithms?

Techniques include algorithm optimization, data structure selection, parallelization, code profiling, and using more efficient programming languages or libraries. Also, consider approximations and trade-offs between accuracy and speed.

What's the difference between "computational costs" and "time complexity"?

"Computational costs" is a broader term encompassing all resources used during computation, while "time complexity" specifically refers to how the execution time of an algorithm grows with the input size, often expressed using Big O notation.

Are there tools to measure "computational costs"?

Yes, profiling tools like perf, gprof, and Intel VTune can measure CPU time, memory usage, and other performance metrics. Cloud providers also offer monitoring tools to track resource consumption and associated costs.