AI Analytics PART 2: Enhance Deep Learning Workloads on 3rd Gen Intel Xeon Scalable Processors
 

In the AI world, deep learning (DL) is foundational for any application’s ability to receive and analyze new information and correctly deduce its meaning. Part 2 of this 3-part series addresses DL workloads and how the AI Kit helps developers make it so.

Continuing the momentum from August 5th, this webinar (which is Part 2 in a 3-part series) looks at the Intel® AI Analytics Toolkit from the perspective of deep learning (DL) workloads.

As in … performance benefits and features that can enhance DL training, inference, and workflows.

Join software engineer Louis Tsai for this PART 2 session that delivers insights into the latest optimizations for Intel® Optimization for TensorFlow* and PyTorch which leverage the new acceleration instructions including Intel® DL Boost and BF16 support from 3rd Gen Intel® Xeon® Scalable processors.

Topics covered:

• How to quantize a model from fp32/bf16 to int8 and analyze the performance speedup among different data types (fp32, bf16, and int8) in depth
• Model Zoo for Intel® Architecture and low-precision tools included in the AI Kit
• Efficiencies when building ML pipelines

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Download the Intel® AI Analytics Toolkit for Linux. Find out more. Download now.