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Creating Performant DL Models for Use in Client Applications
Don Brittain, NVIDIA
Find out what it takes to bring the benefits of deep learning to applications that run at interactive speeds. We'll explain how to think about inference performance throughout the DL development pipeline, covering topics like network design, training considerations, debugging, profiling performance, and optimizing GPU-based code for fastest throughput using tensor core acceleration. Our talk is aimed at application programmers and other AI practitioners, but it should also be accessible to program designers and project managers interested in incorporating AI features into their products.