High performance computing (HPC) refers to the practice of aggregating computing power in a way that delivers much higher performance than one could get out of a typical desktop computer or workstation in order to solve problems in science, engineering, or business. HPC is usually realized by means of computer clusters or supercomputers. Interestingly, the June 2019 edition of the list of TOP500 supercomputer sites marks a milestone in its history because, for the first time, all 500 systems deliver a petaflop or more. But looking at the development of single core performance reveals that it has stopped growing due to heat dissipation and energy consumption issues. As a result, substantial performance growth has started to come only from parallelism, which, in turn, means that sequential programs will not run faster on successive generations of hardware.
Many academic disciplines have been using HPC for research. For example, HPC has become important in systems medicine for Alzheimer's research, in biophysics for HIV-1 antiviral drug development, in earth system sciences for weather simulations, in material science for discovering new materials for solar cells and LEDs, and in astronomy for exploring the universe. Usage statistics of academic supercomputing centers, which have started offering HPC as a commodity good for research, show a high diversity of scientific disciplines that make use of HPC in order to address unresolved scientific problems with computational resources that have been unavailable in the past. These statistics are also an indicator for other scientific disciplines that have hardly used HPC to solve their research problems. Undoubtedly, several of these other research areas will hardly benefit from HPC, for example, because their research is not computationally intensive. But there are also areas where using massive computational resources can help solving scientific problems. One of these areas is Management science (MS), including its strong link to economics.