Sentence examples for memory requirements when from inspiring English sources

This paper addresses the impact of vertical elasticity for applications with dynamic memory requirements when running on a virtualized environment.

There may be high memory requirements when saving large "top-maps" to PNG files, thus using smaller neuron sizes is preferred.

We take advantage of the mesh structure on a block-by-block basis to implement these numerical operators efficiently, and achieve computational speed with modest memory requirements when compared to explicit sparse matrix storage.

This would dramatically reduce the computational and memory requirements when implementing MI.

We recognize that some of the tools listed above have limitations with respect to memory requirements when dealing with large data files and expanded/compact forms of the schema.

This strategy aims to reduce the memory requirement when analyzing large-scale datasets.

For instance, in assembly projects removing redundant sequences will help to reduce the memory requirements, but when the clusters are contaminated with false positives then the clustering will remove many sequences that may be important for an optimal assembly.

There are two main applications: (i) when defeaturing models so that finite element analysis may be carried out more quickly and with lower memory requirements, and (ii) when performing iterative design based on finite element analysis.

However, the number of states is still exponential, which lead to higher memory and processing time requirements when the number of channels increases since the full-state transition matrix is used to obtain exact results.

We would like to emphasize that this particular GPU-based motion estimation scheme is an alternative to consider in terms of Mpixel/s compared to other purpose systems used for such motion-estimation algorithms, although the algorithm features create a bottleneck, specifically when memory requirements are increased in each stage, with an upward trend.

In the previous section we proposed two algorithms to tackle the memory requirements of the BBA when dealing with large image sets: the solution is to reduce the amount of processed data to a lower, but sufficient, number of tie-points.