One year ago, we announced the creation of the IBM Research AI Hardware Center, a global research hub headquartered in Albany, New York. Building on work of the last few years, the launch of the Center initiated the next phase in a long-term effort to combine evolving, fundamental advances in AI with new computing accelerators, technologies, and architectures designed and optimized specifically for AI computation. Launching the Center was our way to invite industrial and academic partners to join us in the development and productization of AI hardware, essential to meeting the computational demands of the emerging broad AI era. Our inherently energy efficient technologies aim to meet the demand for computational power that AI applications and software advances require.
The Path to 1000x
The Center is taking a holistic, end-to-end approach to AI hardware, spanning the computing stack all the way from fundamental materials research to AI workloads. Our goal is to improve compute performance efficiency 1,000x by 2029, with the annual delivery of new AI accelerator cores, targeting 2.5X improvement per year. We’ve more than doubled that gain in the first year.
The Center is working on several projects in tandem that will help us reach this goal. We are a global leader in approximate computing architecture and software techniques for deep learning with our Digital AI Cores. The Center also develops Analog AI Cores, paving a path to ideal analog core behavior by combining materials, device, and algorithmic innovations. Other innovations in heterogeneous integration chip packaging aim to eliminate memory bandwidth bottlenecks. And, we are creating a software ecosystem for AI hardware tools, as well as an AI testbed environment and ecosystem for AI tool exploration and assessing workloads.
We are now joined by 10 enterprise and academic institutions in our AI Hardware Center. As part of our AI testbed, members have access to Rennslaer Polytechnic Institute’s AiMOS supercomputer — one of the most powerful — and energy-efficient — supercomputers in the world as well as technologies created, developed, tested, and matured in our unparalleled research cleanroom facility in Albany, NY.
Our members collaborate with us in a variety of ways. They can use early access to new hardware technologies and our emulation platform to develop application software before hardware is commercialized. Some of our members are testing our AI for manufacturing automated templates to create custom optimized models for manufacturing controls. Other members use IBM AI tools to create new AI models for enterprise workloads, assessing accuracy and performance. With our equipment, consumable and foundry partners, we are perfecting process technologies for new analog device elements and building testchips. Likewise, we are developing and testing 3D packaging technologies and consumables to eliminate memory bandwidth bottlenecks in AI training. We are partnering with IBM Systems and IBM Cloud teams to bring our AI hardware technologies to our IBM clients.
Year One Results
AI Hardware Center researchers in the Albany hub and global network have already leveraged the Center for research breakthroughs. For example, researchers have published papers ultra-low precision training and inference of deep neural networks and analog materials advances. The IBM Journal of Research & Development focused its fourth quarter 2019 issue on AI hardware advances.
Our outlook for 2020 is bright. We anticipate new members joining the Center throughout the year. Many of our latest innovations are coming together in new 2020 Digital and Analog AI testchips. We will show our progress against our ambitious roadmap to improve compute performance efficiency 1000x, with increasingly complex workloads. In 2020 we will see our technologies become central to improving AI technology’s environmental sustainability by supporting expanding AI workloads while reducing carbon footprint. The new AiMOS supercomputer at RPI will fuel rapid progress on AI core technology and AI hardware. If you think computers and AI have dramatically changed the world, wait until you see what’s next.
In our paper “Extraction of organic chemistry grammar from unsupervised learning of chemical reactions,” published in the peer-reviewed journal Science Advances, we extract the "grammar" of organic chemistry's "language" from a large number of organic chemistry reactions. For that, we used RXNMapper, a cutting-edge, open-source atom-mapping tool we developed.
Founded in March 2020 just as the pandemic’s wave was starting to wash over the world, the Consortium has brought together 43 members with supercomputing resources. Private and public enterprises, academia, government and technology companies, many of whom are typically rivals. “It is simply unprecedented,” said Dario Gil, Senior Vice President and Director of IBM Research, one of the founding organizations. “The outcomes we’ve achieved, the lessons we’ve learned, and the next steps we have to pursue are all the result of the collective efforts of these Consortium’s community.”
The next step? Creating the National Strategic Computing Reserve to help the world be better prepared for future global emergencies.
IBM is supporting marine research organization ProMare to provide the technologies for the Mayflower Autonomous Ship (MAS). Named after another famous ship from history but very much future focussed, the new Mayflower uses AI and energy from the sun to independently traverse the ocean, gathering vital data to expand our understanding of the factors influencing its health.