Sentence examples for achieve computational efficiency from inspiring English sources

The phrase "achieve computational efficiency" is correct and usable in written English.
You can use it when discussing the optimization of algorithms, processes, or systems to perform tasks with minimal resource usage.
Example: "The new algorithm was designed to achieve computational efficiency, allowing it to process data faster while using less memory."
Alternatives: "attain computational efficiency" or "realize computational efficiency."

Exact(15)

To achieve computational efficiency on parallel computers, the linear system was treated by an inverse matrix method (a sparse matrix vector multiplication).

A mesoscale description is employed for representing the heterogeneous behaviour of masonry units, mortar joints and brick-mortar interfaces, whereas a domain partitioning approach allowing for parallel computation is used to achieve computational efficiency.

However, most existing algorithms cannot achieve computational efficiency and accuracy simultaneously.

They achieve computational efficiency by adapting the sampling frequency and the filter order according to the input signal local variations.

The SVR based uncertainty quantification (UQ) algorithm in conjunction with Latin hypercube sampling is developed to achieve computational efficiency.

Therefore, we also applied the model order reduction (MOR) scheme to this coupled multiphysical problem in order to achieve computational efficiency.

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Similar(45)

Instead, the algorithm computes a k-mer based distance between pairs of input sequences and achieves computational efficiency.

In this study, a surrogate based approach using General High Dimensional Model Representations (GHDMR) is employed for achieving computational efficiency in quantifying uncertainty.

The main advantages of MC-SSL over SSL are (a) support for end-to-end security in the presence of partially trusted proxies, and (b) selective data protection for achieving computational efficiency important to resource-constrained clients and heavily loaded servers.

We propose CARAT, a binary-trait association testing approach based on a mixed-effects quasi-likelihood framework, which exploits the dichotomous nature of the trait and achieves computational efficiency through estimating equations.

Although achieving computational efficiency relative to commonly used second order implicit schemes has been the motivating factor, this study focuses on temporal order analysis of the high order schemes on the collocated grid.

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