The motivation to use OpenGL stems from limitations of CPU processing power when we are faced with the task of visualizing millions of data points and doing it fast (sometimes even in real time).
Modern computers have powerful GPUs that are made for fast visualization-related computations (such as games), and there is no reason why they can't be used for science-related visualizations.
Actually, there is at least one drawback of writing hardware-accelerated software that is hardware dependent. Modern graphics cards require proprietary drivers which are sometimes not available on the target platform/machine (the user's laptop, for example). Even when available, sometimes installing the required dependencies on-site is not what you want to spend your time on, while all you want is to present your findings and demonstrate your research results. This is not a showstopper but you should bear this in mind, and measure the benefits and costs of introducing this complexity in...