The Importance of Hardware to Cognitive Computing

Posted on

“Back when the world shifted from the horse and buggy to the automobile, paved roads were needed to enable people to enjoy the full benefits of the internal combustion engine. So roads were paved and, eventually, the highway was invented. The same will be true in today’s transition from conventional computing to cognitive computing,” writes Scott Crowder of IBM Power Systems.  In a recent article Mr. Crowder breaks down the role that hardware is playing in cognitive computing. Today, let’s take a  look at some of his thoughts.

Cognitive computing hitting the mainstream

Mr. Crowder sees the adoption and interests by universities and recent U.S. supercomputer projects as a key sign that cognitive computing will break through to the mainstream. He writes, “In the last few months, I’ve witnessed the beginning of a sea change in the way people at the forefront of computer science think about the future of our field. Faculty members at universities are showing a keen interest in cognitive systems. And I’m not talking just about algorithms and software. They want to discuss the processor and system technologies that will support a new generation of applications and a new era of computing.”

Two new supercomputers are also being developed using hardware built for big data and architecture that has data-centric computing. The project leaders are also adopting software-defined storage to more efficiently manage data-intensive tasks. These new super computers under the “CORAL” project are expected to be delivered in 2017 and will perform five to seven times faster than other supercomputers in the U.S.

 The role of hardware

“I expect advances in processors, system design, accelerators and storage to come in waves over the next few years,” writes Mr. Crowder. For example already IBM’s Power systems which were built to support big data are adapting nicely to the needs of cognitive computing due to their “superior throughput for transferring data back and forth between memory and the processor, and because of their ability to execute more computing processes concurrently.”  Mr. Crowder also points out that accelerators will be a key element in cognitive computing and already are used to support machine learning applications.

Mr. Crowder expects the coming years to be an exciting time in hardware as more companies look to harness the power of cognitive computing.