By Rich Uhlig
We find ourselves in a world awash with data growing at an unprecedented rate. And that data is changing in nature with respect to how and where it is collected as we blanket the planet with new sensing technologies. Cameras, microphones and location sensors in our smart phones, attached to our vehicles and embedded in the environments in which we live and work are shifting the flows of data between centralized data centers and the network edge.
At the same time, Moore’s Law continues to expand what is possible to build in computing systems. The question is less about whether we can expect the economic benefits of Moore’s Law to continue (i.e., further reductions of cost per device over time) and more about whether we can manage the design and programming complexity that it affords.
As I discussed during my presentation at the DARPA Electronics Resurgence Initiative (ERI) Summit in Detroit this week, continuing to achieve the types of gains Moore’s Law enables requires work that cannot be done in silos. Aligned to the ERI mission, Intel is pushing this forward through industry and academic collaborations. To move from lab research to real-world impact requires a truly integrated systems view and a commitment to collaboration across a spectrum of research areas.
That is our approach at Intel Labs. We start with a bold mission, explore solutions, create prototypes and nurture communities to reach the end goal. We work with academia, industry and government organizations such as DARPA at various steps of this process. Together, we explore the development of architectures that use specialized hardware – and software – to solve computing problems more quickly and efficiently. Doing so requires opening our innovations to the broad research community to push every breakthrough further.
Our work with neuromorphic computing provides a good example. We set a goal to achieve several orders of magnitude improvement in energy efficiency (think greater than 1,000 times) for selected workloads like sparse coding, constraint satisfaction, path planning and adaptive control – tasks that we believe will be important as data increasingly must be processed at the edge in realtime and in energy-constrained environments.
We publicly kicked off our neuromorphic work in 2017 when we introduced Loihi, a brain-inspired research chip, to an ecosystem of research partners.
In March 2018, we established the Intel Neuromorphic Research Community (INRC) to further the development of neuromorphic algorithms, software and applications. We have granted INRC members access to accelerate their research through Loihi cloud systems and USB form factors. Their work has spurred new investigations into real-world applications for neuromorphic technologies. We are already seeing a series of publications coming from researchers in the INRC about creative new applications for neuromorphic computing and impressive performance and efficiency results.
Today, we announced Pohoiki Beach, which accelerates this effort by providing greater computational scale and capacity to Intel’s research partners. Pohoiki Beach brings together 64 Loihi chips, each with 128 cores, enabling the efficient modeling of a system of about 8 million neurons. We hope that providing ever-increasing scale of neuromorphic computing platforms will enable the research community to tackle entirely new classes of problems.
This work is a natural extension of the technology innovations we have pioneered for decades. But we can’t do it alone in our silo. To keep pressing forward the logical – and exciting – evolution of Moore’s Law requires collaboration across the entire research ecosystem.
Rich Uhlig is an Intel senior fellow and the director of Intel Labs.