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The so called fourth paradigm [1] of data-intensive discovery often requires significant computational power.
The ability to predict the folding of peptides requires significant computational power and modelling expertise.
Non-linearity, due to convective fluid acceleration, makes this challenging, especially in three dimensional (3D) models; so CFD analyses require significant computational power and time.
However such models require significant computational resources.
The reports were also free: to process (at least) 50 GB of raw logs a day at speed, we would require significant computational resources (by our standards, at least).
Simulating the nonlinear behavior of complex systems requires significant computational effort.
Mining Bitcoins requires significant computational resources.
Obtaining statistically reliable numerical simulations of light scattering by cometary dust particles requires significant computational resources.
However, the training of large datasets requires significant computational resources and can take a long time.
Quantum chemical calculations and feature selection procedure requires significant computational time.
The GPR method provides high-quality meshes but requires significant computational cost.
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