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2017 GTC San Jose

S7359 - Performant Deep Reinforcement Learning: Latency, Hazards, and Pipeline Stalls in the GPU Era ... and How to Avoid Them

Session Speakers
Session Description

The headache of latency, hazards, and pipeline stalls has reared its head again, taking a new form in the GPU era. In the realm of deep reinforcement learning, stateful, interactive simulation-based workloads push this to the extreme, necessitating a handoff to the simulator on every iteration - and that simulator may not even be running on the same machines as the deep reinforcement learning model! We'll explore lessons learned on how to avoid these performance degrading modern hazards. Attendees will learn tricks and techniques - including approaches to pool multiple concurrent simulations for use with single networks - that they can employ in their own systems to increase performance with their deep reinforcement learning workloads.


Additional Session Information
Intermediate
Talk
AI Startup Accelerated Analytics Deep Learning and AI Intelligent Machines and IoT Performance Optimization
Software
50 minutes
Session Schedule