Intelligent Silicon for AI at Scale
November 19 (Thursday) 2020
11:30 am to 12:30 pm (EST)
Abstract
Building AI systems at scale is hard. As the prediction accuracy of learning systems improves with larger data and models, the computational requirements grow non-linearly. This challenge is compounded with emergent trends in AI such as reinforcement learning, cloud to edge orchestration, and real-time decision making. While much of the AI revolution has been enabled by hardware, its forward-looking evolution is limited by the end of Moore’s law.
This talk explores the role of intelligent silicon in enabling AI at scale. Case studies in silicon systems design and manufacturing systems are used to highlight the infrastructure challenges of scaling-out real-life AI applications. Intelligent silicon using Micron’s 3D Xpoint storage class memory is emerging as one of the key enablers of scale-out infrastructure. Key new features such as memory virtualization, memory and storage convergence, and temp storage acceleration are analyzed in context of their impact cloud-to-edge data pipeline orchestration.
Biography
Samir Mittal is Corporate Vice-President (3DXP Systems Solutions Engineering) at Micron Technology. He is an engineering leader with specialization in video analytics, real-time learning, and storage infrastructure. He currently leads Micron’s 3DXP Storage Class Memory teams in building next-generation compute systems for new and emerging AI applications. Prior to joining Micron, Samir was the CEO and founder of SCUTI AI, a startup focused at the intersection of deep learning and scale-out infrastructure. Samir’s career has spanned SanDisk (data center products), Qumu (enterprise video), and Seagate (storage). Samir has a PhD from the Ohio State University specializing in signal processing and control systems.