Speakers
Keynote Speaker
J. Joshua Yang, University of Southern California
Abstract:
Memristors can be broadly categorized into diffusive memristors and drift memristors, based on their reset switching mechanisms. Diffusive memristors reset via the diffusion of mobile species under zero electrical bias, exhibiting dynamics that closely mimic biological ion behavior. This unique characteristic enables efficient neuromorphic computing. In contrast, drift memristors reset through the drift of mobile ions under an electric field, offering highly stable analog resistance levels ideal for constructing neural networks for analog computing. This presentation will highlight recent advancements in memristor devices, arrays, and their application demonstrations, showcasing their potential in emerging computing paradigms.
Biography:
J. Joshua Yang is a professor of the Department of Electrical and Computer Engineering at the University of Southern California. His current research interest is Post-CMOS hardware for neuromorphic computing, machine learning and artificial intelligence, where he published several pioneering papers and holds 120 granted US Patents. He is the Founding Chair of the IEEE Neuromorphic Computing Technical Committee and the director of USC-Airforce Center of Excellent on Neuromorphic Computing. He was elected to the IEEE Fellow and the National Academy of Inventors (NAI) Fellow for his contributions to resistive switching materials and devices for nonvolatile memory and neuromorphic computing.
Invited Speakers Session: New Frontiers in Neuromorphic Computing- How Can we Compute, and at What Scales?
In this special session, four esteemed speakers with complementary backgrounds will cover various topics from the abstract question of what we can compute, to modern artificial intelligence workloads, to the push for extending these workloads and compute kernels to the level of advanced scientific research & heterogeneous integration. The session will be held on the afternoon of December 16th.
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Christof Teuscher, Professor, Portland State University
Title: Alternative ways of computing: what computes, what doesn’t?
Abstract: In 1936, Alan Turing laid the theoretical groundwork for modern computing science by defining what would later become known as a universal Turing machine (UTM). According to the Church-Turing (CT) thesis—a touchstone of modern computing theory—a UTM can carry out any effective computation, or, in other words, it can simulate any other machine capable of performing a well-defined computational procedure. But does a UTM really capture the essence of any and all forms of theoretical and physical computing? Or, are there alternative forms of computing? Forms of computing that are more efficient or more expressive? Let’s find out in this presentation!
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Jeff Zhang, Assistant Professor, Arizona State University
Title: Reliable Deep Learning Inference: From Hardware to Systems
Abstract: To enable more sustainable AI/ML, the development of hardware accelerators and custom systems has significantly enhanced energy efficiency for both training and inferencing. However, faults that may arise from design, manufacturing, or operational factors can impede the deployment and utilization of these advanced hardware and system solutions. This presentation will examine the impact of permanent faults and soft errors on systolic array-based accelerators, alongside effective mitigation techniques. Additionally, we will discuss strategies for achieving high Quality of Service (QoS) inference under fluctuating workloads at the system level.
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Robinson Pino, Program Manager, Department of Energy
Title: Emerging Computing Technologies for Advanced Scientific Computing Research
Abstract: Advances in emerging computing technologies offers potentially new opportunities and capabilities for the advancement of the U.S. Department of Energy (DOE) and Office of Science mission. The DOE Office of Science operates scientific infrastructure, supporting some of the nation’s most advanced intellectual discoveries, spanning the country and including 30 world-class user facilities from supercomputers to accelerators. This talk will present a brief overview of research and development activities in the areas of Artificial Intelligence, Neuromorphic Computing, Microelectronics, and Advanced Wireless at the DOE, Office of Science, Advanced Scientific Computing Research program office.
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Brian Hoskins, Program Manager, NATCAST
Title: Developing Platforms for AI Research and Beyond
Abstract: Experimental validation of future systems is a critical component the hardware development process, allowing for insights not solely available in theory as well as opportunities to discover to phenomenon not initially envisioned. This talk will cover recent developments and the applications of developing a 2-Terminal memory device test platform and the insights gained from experimental validation of this system, particularly through the use of defect tolerant algorithms and study of underlying device statistics. Based on these positive results, the prospects of developing future systems and vehicles for accelerating R&D across various technology domains will be explored.