As microprocessors push up against the limits of miniaturization, many are reflecting on what the post-silicon era has in store. Recently Sandia National Laboratories published an article describing the steps it is taking to extend the pace of computational progress over the coming decades. Some of the forward-leaning technologies include self-learning supercomputers and systems that greatly outperform today’s best crop while using less energy.

As history tells us, many of today’s established technologies would have seemed impossible at one time. Think about explaining Internet-connected smart phones to a pre-mobile, pre-Web generation – and that wasn’t that long ago.

“We think that by combining capabilities in microelectronics and computer architecture, Sandia can help initiate the jump to the next technology curve sooner and with less risk,” said Rob Leland, head of Sandia’s Computing Research Center.

Leland is leading a new initiative focused on next-generation computing called Beyond Moore Computing that encompasses Sandia’s efforts to advance computing technology beyond the exponential trend that was observed by Gordon Moore in 1965.

Moore’s law can be extended for a few more process shrinks but the cost is no longer feasible from an energy perspective. The industry needs technology that uses less energy at the transistor device-level, expressed Leland.

Scientists at Sandia anticipate that multiple computing device-level technologies will evolve to fill this gap, as opposed to one dominant architecture. So far, there exist about a dozen candidates, including tunnel FETs (field effect transistors), carbon nanotubes, superconductors, and paradigm-changing approaches like quantum computing and brain-inspired computing.

Leland makes the case that Sandia Labs, a multi-program laboratory operated by Sandia Corporation, a subsidiary of Lockheed Martin Corp., is well positioned to shape future computing technology.

The lab has decades of supercomputing experience, both on the hardware and software side, extending to capability computing and capacity computing. Leland references two key facilities in particular that will contribute to next-gen computing: the Microsystems and Engineering Sciences Applications (MESA) complex, which carries out chip-level R&D; and the Center for Integrated Nanotechnology (CINT), a Department of Energy Office of Science national user facility operated by Sandia and Los Alamos national laboratories.

This is really an inflection point, where it is difficult to predict what tomorrow’s computers will look like. “We have some ideas, of course, and we have different camps of opinion about what it might look like, but we’re really right in the midst of figuring that out,” Leland said.

One way that computing’s progress has been limited is the mandate for backwards software compatibility. Many computers are running code that was optimized to run on a different architecture.

“To break out of that, we have to find different architectures that are more energy efficient at running old code and are more easily programmed for new code, or architectures that can learn some behaviors that once required programming,” notes Erik DeBenedictis of Sandia’s Advanced Device Technologies department. He expects that computers are about a decade away from being able to manage both old and new code in an efficient manner.

DeBenedictis is pushing for breakthroughs beyond the transistor level. He cites cognitive computers and technologies that move data more efficiently as being crucial for the kinds of big data problems that are becoming so prominent.

This new generation of cognitive computers would be self-learning and able to share some of the programming burden. DeBenedictis makes the point that “while computers have gotten millions of times faster, programmers and analysts are pretty much as efficient as they’ve always been.” Smarter computers have the promise of ameliorating this bottleneck.

As for a timeline, Advanced Device Technologies department manager John Aidun says that post-silicon technology is coming sooner than one might think. Looking through the lens of national security, Sandia thinks this new tech will be needed sooner than industry would develop it on its own. Hence, the concerted efforts in this direction. Aidun estimates Sandia could have a prototype within a decade.

The lab is working to accelerate the process by identifying computer designs that leverage new device technologies and demonstrate fabrication steps that would lower the risk for industry. Mobile computing is an area that’s getting a lot of attention. Mobile meets a lot of the requirements of UAVs and satellites. On-board processing for satellites and other sensors would mean less need for data transfer.

Again, with history as a guide, the next big thing in computing may be an extention of a current technology, a mix of technologies (as in heterogeneous computing) or it might be something entirely different and new.