The rise of more creative and powerful simulation, modeling, and computation along with a superlinear expansion in both the variety and size of data is transforming science [1, 2].
However, nowadays computers are much more powerful and Monte Carlo simulations are widely used.
Moreover, the performance of the GPU is compared to the SSE+OpenMP CPU implementation, and it is quantitatively determined that a highly optimized CPU program can be competitive for a wider range of simulation sizes, whereas GPU computing becomes more powerful for large-scale simulations.
It goes like this: Everyone knows that historically, as computers became more powerful, programmers started making simulations -- mimicking real-life situations in software.
A more powerful potential application of the model is the simulation of expected immunogenicity incidence in a human population against a therapeutic protein.
The simulations demonstrate that epistatic models can be more powerful than the additive model (Figure 5).
There has been a significant increase in the use of spectral simulation in many areas of clinical research in the past decade, due greatly to improved access to more powerful mainstream computers and open source simulation software packages.
In silico simulation is much more powerful and reliable than before for the bioprocess analysis and optimization in the fields of metabolic engineering and systems biology.
These variations on Fisher's product test have proven more powerful than the original test in simulation studies (18).
In the past three decades, as simulations have grown more powerful, scientists have been able to test out all kinds of factors impactors of various sizes, approaching at various speeds and angles, hitting an Earth spinning at various rates.
