IBM’s Post-Moore Vision: Bits Plus Neurons Plus Qubits
Dario Gil, IBM’s relatively new director of research, painted a intriguing portrait of the future of computing along with a rough idea of how IBM thinks we’ll get there at last month’s MIT-IBM Watson AI Lab’s AI Research Week held at MIT. Just as Moore’s law, now fading, was always a metric with many ingredients baked into it, Gil’s evolving post-Moore vision is a composite view with multiple components.
“We’re beginning to see an answer to what is happening at the end of Moore’s law. It’s a question that has been the front of the industry for a long, long time,” said Gil in his talk. “And the answer is that we’re going to have this new foundation of bits plus neurons plus qubits coming together, over the next decade [at] different maturity levels – bits [are] enormously mature, the world of neural networks and neural technology, next in maturity, [and] quantum the least mature of those. [It] is important to anticipate what will happen when those three things intersect within a decade.”
Not by coincidence IBM Research has made big bets in all three areas. It’s neuromorphic chip (True North) and ‘analog logic’ research efforts (e.g. phase change memory) are vigorous. Given the size and scope of its IBM Q systems and Q networks, it seems likely that IBM is spending more on quantum computing than any other non-governmental organization. Lastly, of course, IBM hasn’t been shy about touting Summit and Sierra supercomputers, now ranked one and two in the world (Top500), as the state of the art in heterogeneous computing architectures suited for AI today. In fact, IBM recently donated a 2 petaflops system petaflops, Satori, to MIT that is based the Summit design and well-suited for AI and hybrid HPC-AI workloads.
Gil, who was promoted to director of IBM Research last February, and has begun playing a more visible role. For example, he briefed HPCwire last month on IBM’s new quantum computing center. A longtime IBMer (~16 years) with a Ph.D. in electrical engineering and computer science from MIT, Gil became the 12thdirector of IBM Research in its storied 74-year history. That IBM Research will turn 75 in 2020 is no small feat in itself. It has about 3,000 researchers at 12 labs spread around the world with 1,500 of those researchers based at IBM’s Watson Research Center in N.Y. IBM likes to point out its research army has included six Nobel prize winners and the truth is IBM research effort dwarfs those of all but a few of the biggest companies.
In his talk at MIT, though thin on technical details for the future, Gil did a nice job of reprising recent computer technology history and current dynamics. Among other things he looked at how the basic idea of separating information – digital bits – from the things they represent and how for a long time that proved incredibly powerful in enabling computing. He then pivoted noting that ultimately nature doesn’t seem to work that way and that for many problems, as Richard Feynman famously suggested, quantum computers based on quantum bits (qubits) are required. Qubits, of course, are intimately connected to “their stuff” and behave in the probabilistic ways as nature does. (Making qubits behave nicely has proven devilishly difficult.)
Pushing beyond Moore’s law, argued Gil, will require digital bits, data-driven AI, and qubits working in collaboration. Before jumping into his talk it’s worth hearing his summary of why the pace of progress even as experienced in Moore’s law’s heyday would be a problem today. As you might guess both flops performance and energy consumption are front and center along with AI’s dramatically growing appetite for compute...
For the rest of this article please visit the site of sister publication HPCwire.