September 25th, 2019 – Decades ago, only the largest and most sophisticated companies and institutions had access to “high performance computing” technologies. In practice, this meant that only large government agencies, high tech companies, and a small cadre of elite academic institutions harnessed the power of “supercomputers.” Using these supercomputers, such entities delivered new scientific discoveries and remarkable insights, in areas ranging from genomics and financial risk modeling to emerging uses such as machine learning and autonomous vehicles.
Within the behavioral sciences, measurement specialists also began conceiving of uses of advanced computing power. For example, the idea of “computational psychometrics” appeared, triggering calls to explore how advanced computing power could inform the development of mathematical models, intelligent learning applications, virtual assessments, and computer simulations of large-scale, complex data (Von Davier, Deonovic, Yudelson, Polyak, & Woo, 2019). Vendors also began offering Artificial Intelligence (AI) based methods as a practical means for developing, administering, and scoring operational assessments, which required increasing amounts of computing power (Putka & Dorsey, 2019). In the past, accessing added computing power meant simply upgrading to the latest laptop, desktop, or local server. However, as algorithmic complexity and dataset sizes increased, such solutions simply stopped being affordable or viable. Instead, power users turned to cloud-based systems, either public (e.g., Amazon, Google, Microsoft) or private, to gain a computational advantage.
Cloud-based systems offer a number of improvements, including: 1) scalability – such systems can provision as much computing capacity as needed, 2) dependability – most public cloud data centers are designed for 24/7 operations, without limitations such as power interruptions, and 3) convenience – analyses can be run and accessed from anywhere with Internet connectivity. As a practical example of why such cloud-based features matter—even for a relatively small company like HumRRO—we offer below a brief case example from our own recent work.