Sentence examples for benchmarks of computational from inspiring English sources

Even taking into account our current inability to resolve Open Questions 1 3, the hierarchy of complexity classes depicted in Figure 2 ranging from \ \textbf{P}\) to \ \textbf{EXP}\) represent the most robust benchmarks of computational difficulty now available.

3.4.3 Parallel, probabilistic, and quantum complexity Even taking into account our current inability to resolve Open Questions 1 3, the hierarchy of complexity classes depicted in Figure 2 ranging from \ \textbf{P}\) to \ \textbf{EXP}\) represent the most robust benchmarks of computational difficulty now available.

In this article we discuss the statistical models implemented in BGLR (Statistical Models, Algorithms, and Data), present several examples based on real and simulated data (Application Examples), and provide benchmarks of computational time and memory usage for a linear model (Benchmark of Parametric Models).

The main objective of this test is benchmarking of computational tools.

This set of structures and the physical insight they contribute into internal hydration will be useful for the development and benchmarking of computational methods for artificial hydration of pockets, cavities, and active sites in proteins.

Such bias is potentially problematic where the published data could be misleading as basis for the development and benchmarking of computational tools for B-cell epitope prediction.

To evaluate existing models and new codes in development, we conduct a benchmarking study of computational fluid dynamics (CFD) models for lava flow emplacement.

This paper presents analytical results for high-speed leading-edge noise which may be useful for benchmark testing of computational aeroacoustics codes.

In order to assess existing models and guide the development of new codes, we conduct a benchmarking study of computational fluid dynamics (CFD) models for lava flow emplacement, including VolcFlow, OpenFOAM, FLOW-3D, COMSOL, and MOLASSES.

In turn, Fig.  3 summarises the benchmark of the computational time.

The benchmarking of linear computational complexity holds up for all regions of parameter space { qfix,  qfluct,  p}, except exceedingly close to the rigidity transition when qfix → 0 and qfluct → 1, where the VPG scales as O(N) to identify all constraints as independent or redundant.