Stanford Seminar – Erudite: Prototype System for Computational Intelligence

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Overview

Since the rise of deep learning in 2012, much progress has been made in deep-learning-based AI tasks such as image/video understanding and natural language understanding, as well as GPU/accelerator architectures that greatly improve the training and inference speed for neural-network models. As the industry players race to develop ambitious applications such as self-driving vehicles, cashier-less supermarkets, human-level interactive robot systems, and human intelligence augmentation, major research challenges remain in computational methods as well as hardware/software infrastructures required for these applications...

Syllabus

Introduction.Erudite: A Low-Latency, High-Capacity, and High- efficiency System for Computational Intelligence.C3SR Core Faculty.Al Application Pipeline Example - Watson Jeopardy 2011.Automatic Generation of Sports Highlight and Analytics.Automatic Conference Reviewer Assignment.C3SR Al Task Libraries.Person Parsing.Example Application DL Inference Flow in the Cloud.Hardware Comparison - Same Model and Framework.Importance of Model Data Loading in DL Inference.Hardware for Watson Jeopardy! 2011.FlatFlash-Storage-class Memory.FlatFlash Architecture.Example: Performance Benefit for Graph Computation.A Simplified View of IBM Newell with NVIDIA Volta GPUs.Starting Point - Data Access Challenge (HBM).Starting Point - Data Access Challenge (DDR).Iterative Solver Example- If matrix fits into Host Memory.Triangle Counting Example.MCN Near-Memory Acceleration for Existing Scalable Applications performing computation near data.Comparison Against a Traditional SPARC Cluster.Erudite Step 1.