This talk will cover AI hardware architecture and In-Memory computing paradigms tailored for Edge applications with scalability towards TinyML workloads. We will look at the intricacies of novel hardware architectures optimized for resource-constrained devices, enabling efficient and real-time inference of machine learning models. We will look at real-world examples to discover how In-Memory Neural Processors further manage data movement and computation to enhance edge AI systems’ performance and energy efficiency while maintaining reconfigurability.
Schedule
Timezone: PDT
Empowering the Edge: Advancements in AI Hardware and In-Memory Computing Architectures for TinyML
Nitin CHAWLA, ST Fellow and Director in the Technology R&D
STMicroelectronics
Nitin CHAWLA, ST Fellow and Director in the Technology R&D
STMicroelectronics
Nitin Chawla is an ST Fellow and Director in the Technology R&D (Strategy and Innovation) organization at STMicroelectronics, where he leads the research initiatives in the area of Low Power Neural Networks and In-Memory computing architectures for Edge and Tiny ML applications. Nitin has a major in Electronic Circuits and Systems. He is an alumnus of Stanford University and holds a TRIZ diploma from the Massachusetts Institute Of Technology, Cambridge. He has served in different R&D and product organizations over the last 25 years. Before joining STMicroelectronics, he was the Chief Scientist of the HLS Product Division at Mentor Graphics Corporation based in Oregon, USA. Nitin has over 40+ US patents and more than 30 conference and journal publications.
Schedule subject to change without notice.