In Deep Learning, Inference is where neural networks deliver insights. What started with images has quickly expanding to include speech, NLP, recommender systems and video. As data sets get bigger, networks get deeper and more complex, and latency requirements get tighter, GPUs are the ideal platform to accelerate these workloads, both for high batch and low-latency use-cases. In this talk, you'll learn how inference gets done on GPUs, get the latest on updates on the software stack for Inference including TensorRT inference engine and DeepStream SDK and recommendations on choosing the right GPU for running inference workloads.
Hall: Hall F
Track: General Deep Learning