Sentence examples for high memory requirement from inspiring English sources

Storing 3D texture images in a table for fast mapping computations, instead of evaluating procedures on the fly, however, has been considered impractical due to the extremely high memory requirement.

Although computing devices that have high memory requirement do not normally have problems with memory consumption, traditional variation resampling is often thought to be more appropriate for usage in this environment because it is faster than traditional resampling [58].

On the other hand, the utilisation of traditional variation resampling is beneficial for computing devices that require more than a single sampling process for every j cycle (for instance, computing devices that have a high memory requirement).

Although this technique proved to be successful for aligning with the small Arabidopsis Col-0 genome, its high memory requirement makes its applicability to a human genome still questionable (Li and Homer, 2010).

The latest implementation as of this writing (v1.24) is very fast, but only runs on 64-bit Linux, uses single- instead of double-precision arithmetic, and has a high memory requirement.

We also note that an existing VBEM algorithm implementation, TIGAR, does not provide a significant improvement over Gibbs sampling in terms of computational time in our examples, as well as having a very high memory requirement.

While this can cause high memory requirements, querying only requires OLAP functions to fetch the data without the necessity to perform complex joins between tables.

These techniques can avoid the high memory requirements of DA-MCMC, and under certain conditions produce the exact marginal posterior distribution for parameters.

On the other hand, having a large number of elements is often necessary for properly describing complex microstructures, ultimately leading to extremely time-consuming computations and high memory requirements.

In the proposed scheme, an attempt is made to strike a balance between the long delay caused by the pessimistic and the high memory requirements of the optimistic schemes.

To deal with the high memory requirements and in order to accelerate the numerical evaluation of hereditary integrals, we employ a fast convolution method [2] that reduces the memory cost to O log(N)) and the computational complexity to O(Nlog(N)).