ONLINE: Intel® AI HPC Workshop #2: Deep Learning Module
Date: | Friday, October 9, 2020, 13:30-17:00 |
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Location: | online |
Contents: |
The demand of using Deep Learning techniques in many scientific domains is rapidly emerging and the requirements for large compute and memory resources is increasing. One of the consequences is the need of the high-performance computing capability for processing and inferring the valuable information inherent in the data. The Leibniz Supercomputing Centre (LRZ) has recently installed its new high-end system, SuperMUC-NG. Based on Intel® technology, it targets among others also workloads at the crossroads of AI and HPC. In this session you will learn various optimization methods to improve the runtime performance of Deep Learning algorithms on Intel® architecture. We cover how to accelerate the training of deep neural networks with TensorFlow, thanks to the highly optimized Intel® Deep Neural Network Library (DNNL). We also demonstrate techniques on how to leverage deep neural network training on multiple nodes on an HPC cluster. Schedule: 13:30 - 14:45 Deep Learning – Optimized training instances
14:45 – 15:15 Hands On Session
15:15-15:30: Coffee Break 15:30-16:30 Deep Learning – Optimized inference instances
16:30 - 17:00 Hands On Session
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Prerequisites: |
Basic knowledge of Python Participation (or comparable previous knowledge) in
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Language: | English |
Contact: |
G Anthony Reina (Intel®), Ravi Panchumarthy (Intel®) |
Material: | https://doku.lrz.de/download/attachments/55902601/LRZ_INTEL_AI_workshop_2.pdf (see https://doku.lrz.de/display/PUBLIC/Data+Analytics%2C+Big+Data+and+Machine+Learning+Training+Courses+at+LRZ) If you attended this course, please don't forget to rate it. We highly appreciate your feedback: |