The design and analysis of numerical methods are usually guided by the following: (a) von Neumann analysis using Fourier series expansion of unknowns, (b) the modified differential equation approach, and (c) a more generalized approach that analyzes numerical methods globally, using Fourier–Laplace transform to treat the total or disturbance quantities in terms of waves. This is termed as the global spectral analysis (GSA). GSA can easily handle non-periodic problems, by invoking wave properties of the field through the correct numerical dispersion relation, which is central to the design and analysis. This has transcended dimensionality of the problem, while incorporating various physical processes e.g. by studying convection, diffusion and reaction as the prototypical elements involved in defining the physics of the problem. Although this is used for fluid dynamical problems, it can also explain many multi-physics and multi-scale problems. This review describes this powerful tool of scientific computing, with new results originating from GSA: (i) providing a common framework to analyze both hyperbolic and dispersive wave problems; (ii) analyze numerical methods by comparing physical and numerical dispersion relation, which leads to the new class of dispersion relation preserving (DRP) schemes; (iii) developing error dynamics as a distinct tool, identifying sources of numerical errors involving both the truncation and round-off error. Such studies of error dynamics provide the epistemic tool of analysis rather than an aleatoric tool, which depends on uncertainty quantification for high performance computing (HPC). One of the central themes of GSA covers the recent advances in understanding numerical phenomenon like focusing, which defied analysis so far. An application of GSA shown here for the objective evaluation of the so-called DNS by pseudo-spectral method for spatial discretization along with time integration by two-stage Runge–Kutta method is performed. GSA clearly shows that this should not qualify as DNS for multiple reasons. A new design of HPC methods for peta- and exa-flop computing tools necessary for parallel computing by compact schemes are also described.