Whatever Happened to Business Supercomputers?
When it came down to business, supercomputers headed in another direction.
It once seemed inevitable -- a surefire thing -- that supercomputers would help businesses tackle the demands imposed by massive databases, complex engineering tools, and other processor-draining challenges. Then, suddenly, both technology and businesses took a different course.
Chris Monroe, co-founder of and chief scientist at quantum computing company IonQ, offers a simple explanation for the abrupt change in interest. “Supercomputers failed to catch on because, although they bring the promise of speed and ability to process large computational problems, they come with a significant physical footprint [and] energy/cooling requirements,” he notes. “When it comes to mainstream adoption, supercomputers never hit the right balance of affordability, size, access, and value-add enterprise use cases.”
New Directions
Supercomputers have traditionally been defined by the fact that they bring together a collection of parallel hardware providing a very high computational throughput and rapid interconnections. “This is in contrast to traditional parallel processing where [there are] a lot of networked servers working on a problem,” explains Scott Buchholz, government and public services CTO and national emerging technology research director for Deloitte Consulting. “Most business problems can be solved either by the latest generation of standalone processors or else by parallel servers.”
The arrival of cloud computing and easily accessible APIs, as well as the development of private clouds and SaaS software, put high-performance computing (HPC) and supercomputers in the rearview mirror, observes Chris Mattmann, chief technology and innovation officer (CTIO) at NASA's Jet Propulsion Laboratory (JPL). “Relegated to science and other boutique use, HPC/supercomputers ... never caught up to modern-day [business] standards.”
Current Adopters
Today, while most businesses have shied away from supercomputers, scientific and engineering teams often turn to the technology to help them address a variety of highly complex tasks in areas such as weather predictions, molecular simulation, and fluid dynamics. “The sets of scientific and simulation problems that supercomputers are uniquely well suited to solving will not go away,” Buchholz states.
Scott Buchholz, Deloitte Consulting
Supercomputers are primarily used in areas in which sizeable models are developed to make predictions involving a vast number of measurements, notes Francisco Webber, CEO at Cortical.io, a firm that specializes in extracting value from unstructured documents.