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Sign up today to attend LIVE SESSIONS covering the latest overviews, insights, and how-to’s on topics that drive our cross-architecture, heterogeneous-compute world—oneAPI, AI, HPC, rendering & ray tracing, video & media, IoT, and more.

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Learn Heterogeneous C++ with SYCL

Wednesday, February 8, 2023 | 9:00 AM IST

Deepen your understanding of heterogeneous C++ programming so you can more effectively create and deploy multi-vendor applications.

 

The past 18 months have seen a growing body of C++ with SYCL code to learn from, including the expert articles covering performance tunability, low-level FPGA implementations, accelerated encrypted computing, GPU-to-SYCL code migration, and much more.

In this session, heterogeneous programming expert James Reinders will help you expand your C++ programming expertise and become a highly effective heterogeneous programmer who creates portable, multi-vendor applications.

Sign up today.

Skill level: All

Featured software

Get Data Parallel C++: the oneAPI implementation of SYCL as part the Intel® oneAPI Base Toolkit— a core set of tools and libraries for developing high-performance, data-centric applications across diverse architectures.


 
James Reinders
Software Engineer, Parallel Programming Expert, Author, Intel

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Optimize End-to-End Transformer Performance on the Latest Intel® Xeon® Processors

Wednesday, February 15, 2023 | 9:00 AM PST

Get best practices from Intel and Hugging Face for optimizing multi-node, distributed transformer model training and inference on 4th Gen Intel® Xeon® Processors.

 

Transformer models are powerful neural networks that have become the de facto standard for delivering advanced performance for tasks such as natural language processing (NLP), computer vision, and online recommendations. (Fun fact: People use transformers every time they do an Internet search on Google or Bing.)

But there’s a challenge: Training these deep learning models at scale requires a large amount of computing power. This can make the process time-consuming, complex, and costly.

This session shares a solution: an end-to-end training and inference optimization for transformers.

Join your hosts from Intel and Hugging Face (notable for its transformers library) to learn:

  • How to do multi-node, distributed CPU fine-tuning for transformers with hyper-parameter optimization using Hugging Face transformers, its Accelerate library, and Intel® Extension for PyTorch
  • How to easily do inference optimization, including model quantization and distillation using Optimum Intel, the interface between the transformers library and Intel® tools and libraries

You’ll also see a showcase of transformer performance on the latest Intel® Xeon® Scalable processors.

Sign up today.

Skill level: Intermediate

Featured software

Get the Intel Extension for PyTorch as part of the Intel® AI Analytics Toolkit or standalone.


Learn more


 
Julien Simon
Chief Evangelist at Hugging Face

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