Computing, since its inception, has been processor-centric, with memory separated from compute. Inspired by the organic brain and optimized for inorganic silicon, NorthPole is a neural inference architecture that blurs this boundary by eliminating off-chip memory, intertwining compute with memory on-chip, and appearing externally as an active memory chip. NorthPole is a low-precision, massively parallel, densely interconnected, energy-efficient, and spatial computing architecture with a co-optimized, high-utilization programming model.
On the ResNet50 benchmark image classification network, relative to a graphics processing unit (GPU) that uses a comparable 12-nanometer technology process, NorthPole achieves a 25 times higher energy metric of frames per second (FPS) per watt, a 5 times higher space metric of FPS per transistor, and a 22 times lower time metric of latency. Similar results are reported for the Yolo-v4 detection network.
NorthPole outperforms all prevalent architectures, even those that use more-advanced technology processes.
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About the Speaker
Dr. Carlos Ortega-Otero is an Sr. Research Staff Member at IBM driven by a passion in Circuit Design, Neuromorphic Chip Architectures, Low-Power Circuits and Physical Design optimizations. He earned his Ph.D. from Cornell University under the guidance of Prof. Rajit Manohar.
Throughout his career, he has worked in groundbreaking projects, including Ultra-Low Power Asynchronous Sensor Network nodes, Medical Implantable Wireless Sensors, The TrueNorth Brain-Inspired Chip, and the NorthPole Project. At IBM, Carlos works under the leadership of Dr. Dharmendra Modha in the Brain-Inspired Computing Group.
He plays key roles in Architecture, Specification, Digital Implementation, Physical Design, Timing Signoff, and Manufacturing teams of the NorthPole Project. Carlos is proud to be part of the Brain-Inspired Computing Group at IBM that continues to shape the future of Integrated Circuits and AI.
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