Sentence examples for quick exploration from inspiring English sources

With the growing scope of embedded computing, specific design objectives demand quick exploration and estimation of design metrics.

In this study, β1 is kept at a relatively low value of 5, which is set for a quick exploration of all the routes in the network.

The use of GAs based on a multi-GPU scheme allowed for quick exploration of feasible solutions with any set of input data.

In this paper we present a mathematical model that, based on these factors, calculates the computation time of pipelined FPGA accelerators and allows for quick exploration of the design space without any implementation or simulation.

Moreover, the floorplanning of the chip strongly determines the thermal profile of the system and a quick exploration of the design space is required to minimize the damage of the thermal effects.

An important evolutionary advantage of recombination is that it allows for a quick exploration of a wide array of genotypes.

The games favored a quick, broad exploration of the design space and facilitated the elicitation of numerous diverse needs and ideas, almost twice as many as produced by the structured approach.

To illustrate the mechanics of the tool, the paper details the cost estimation module that enables quick and intuitive exploration of early stage design in a popular 3D modelling environment.

Our method comprises the following two characteristics: (i) the automatic determination of the position and length of common property motifs by calculating the physicochemical similarity of amino acids, and (ii) the quick and effective exploration of motif candidates that discriminates the positives and negatives by the introduction of genetic programming (GP).

Important features of modern visualization tools include: interactivity; interoperability; efficient data exploration; quick visual data querying; smart visual adjustment for different devices with different dimensions and resolutions; fast panning; fast zooming in or out; multilayered visualization; visual comparison of data; and smart visual data filtering.

Scripting languages (e.g. Python, Perl and Ruby) are ideal for quick prototyping and the exploration of new ideas, but can be too slow or memory inefficient for large datasets.