This Computer Can Hold the Entire Library of Congress Collection, Five Times

HPE has built a new computer for the big data era.

Known as “The Machine” it has enough memory to hold the contents of the Library of Congress five times over.

The Machine prototype can hold 160 terabytes of data, spread across 40 physical nodes.

HPE writes of the prototype:

The prototype unveiled today contains 160 terabytes (TB) of memory, capable of simultaneously working with the data held in every book in the Library of Congress five times over—or approximately 160 million books. It has never been possible to hold and manipulate whole data sets of this size in a single-memory system, and this is just a glimpse of the immense potential of Memory-Driven Computing¹.

Scalability & Societal Implications

Based on the current prototype, HPE expects the architecture could easily scale to an exabyte-scale single-memory system and, beyond that, to a nearly-limitless pool of memory—4,096 yottabytes. For context, that is 250,000 times the entire digital universe today.

With that amount of memory, it will be possible to simultaneously work with every digital health record of every person on earth; every piece of data from Facebook; every trip of Google’s autonomous vehicles and every data set from space exploration all at the same time—getting to answers and uncovering new opportunities at unprecedented speeds.

“We believe Memory-Driven Computing is the solution to move the technology industry forward in a way that can enable advancements across all aspects of society,” said Mark Potter, CTO at HPE and director, Hewlett Packard Labs. “The architecture we have unveiled can be applied to every computing category—from intelligent edge devices to supercomputers.”

Memory-Driven Computing puts memory, not the processor, at the center of the computing architecture. By eliminating the inefficiencies of how memory, storage and processors interact in traditional systems today, Memory-Driven Computing reduces the time needed to process complex problems from days to hours, hours to minutes, minutes to seconds, to deliver real-time intelligence.