CEA-Leti’s chief scientist today issued a forward-looking call to action for the microelectronics industry to create a radically new, digital-communication architecture for the Internet of Things in which “a great deal of analytics processing occurs at the edge and at the end devices instead of in the Cloud”.
Delivering a keynote presentation at the kickoff of ISSCC 2018, Barbara De Salvo said this architecture will include human-brain inspired hardware coupled to new computing paradigms and algorithms that “will allow for distributed intelligence over the whole IoT network, all-the-way down to ultralow-power end-devices.”
“We are entering a new era where artificial-intelligence systems are … shaping the future world,” said De Salvo, who also is Leti’s scientific director. “With the end of Moore’s Law in sight, transformative approaches are needed to address the enduring power-efficiency issues of traditional computing architectures.”
The potential efficiencies of processing data at the edge of networks – e.g. by small computers located near IoT-connected devices – rather than at distant data centers or the Cloud are increasingly cited as long-term goals for the Internet of Things. But the challenges to realizing this vision are formidable. For example, IoT battery-powered devices lack both processing power to analyze the data they receive and a power source that would support data processing.
To break through these barriers, De Salvo called for a “holistic research approach to the development of low-power architectures inspired by the human brain, where process development and integration, circuit design, system architecture and learning algorithms are simultaneously optimized.” She envisions a future in which optimized neuromorphic hardware will be implemented as a highly promising solution for future ultralow-power cognitive systems that extend well beyond the IoT.
“Emerging technologies such as advanced CMOS, 3D technologies, emerging resistive memories, and silicon photonics, coupled with novel brain-inspired paradigms, such as spike-coding and spike-time-dependent-plasticity, have extraordinary potential to provide intelligent features in hardware, approaching the way knowledge is created and processed in the human brain,” she said.
De Salvo’s presentation, “Brain-Inspired Technologies: Towards Chips that Think”, included summaries of key research findings in a variety of fields that will play a role in developing brain-inspired technologies for computing and data-handling requirements of a “hyperconnected” world.