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Run Your GenAI Programs on Intel® Arc™ GPUs

Wednesday, July 31, 2024 | 9:00 AM PT

Learn the best practices and tools for building high-performance generative AI applications on Intel’s budget-friendly GPUs.

 

According to a myriad of trusted tech-focused websites, Intel® Arc™ GPUs offer great price-to-performance value for game development, media creation and, yes, generative AI.

This session focuses on how to implement high-performing GenAI applications on these daily-driver GPUs using Stable Diffusion (SD), Llama 3 quantization, and Intel-optimized extensions for PyTorch and Transformers. You’ll also see a demo on building a chatbot using the RAG technique.

Key learnings:

  • How to deploy SD and large language models on Intel Arc GPUs.
  • How to set up your own GenAI application with a few lines of code.
  • How to quantize Llama 3 with INT4 via Intel AI-optimized software.
  • How to build a chatbot with a RAG engine.

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Skill level: Novice

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Intel, the Intel logo, and Arc are trademarks of Intel Corporation or its subsidiaries.


 
Zhang Jianyu
AI Software Solutions Engineer, Intel
Kai Lawrence Wang
AI Software Solutions Engineer, Intel

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Optimizing Federated Learning Workloads: A Practical Evaluation

Wednesday, August 7, 2024 | 9:00 AM PT

Get a comprehensive evaluation of Intel CPU and GPU performance within the cutting-edge context of federated learning.

 

Federated learning (FL) is a machine learning approach for training models on decentralized edge devices without sharing raw data. Within this framework, organizations can collaborate on model development, models can gain experience from a vast range of data located at different sites, and data privacy can be preserved.

But FL implementation comes with challenges.

This session addresses one of them: Optimizing FL workload performance on CPUs and GPUs.

It leverages the implementation and results of a recent ASUS FL solution for the healthcare industry that significantly boosts efficiency and performance by using Intel® Xeon® processors with Intel® oneAPI and AI tools.

Key learnings:

  • An overview of the ASUS solution—the approach, methodologies, and results.
  • Using Intel AI software stacks and tools to analyze and enhance the performance of CNN models, e.g., VGG19 and EfficientNet, in real medical scenarios.
  • Reviewing performance issues of AI framework and verifying the compatibility of the desired hardware.
  • Collaboratively training a CNN model without sharing private data and images, using the open source FL framework Flower.

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Skill level: All

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Intel, the Intel logo and VTune are trademarks of Intel Corporation or its subsidiaries.


 
Joel Lin
Software Technical Consulting Engineer
Joseph Lu
Assoc. Director Infrastructure Solution Group, ASUSTek
Dr. Lien Chungyueh
Assoc. Professor, Dept of Info Management, NTUNHS

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Profile & Optimize OpenVINO™ Workloads at the Hardware Level

Wednesday, August 14, 2024 | 9:00 AM PT

Get in-depth performance insights for deep learning model-based applications targeting CPU, GPU, and NPU.

 

The OpenVINO toolkit streamlines development, integration, and deployment of performant DL models in domains like computer vision, LLMs, and GenAI.

But given the ubiquity of heterogeneous compute environments, there’s a good chance your models and model-based apps must run on multiple hardware targets. Optimizing for each can take a bit of sleuthing.

This session addresses that issue, showing you how to configure and run analysis on your OpenVINO workloads to uncover bottlenecks on target hardware—CPU, GPU, NPU—using Intel® VTune™ Profiler and Intel® Advisor

Topics covered:

  • The OpenVINO framework to boost AI application performance.
  • Using Intel Advisor for performance modeling and CPU/GPU roofline generation.
  • Using VTune Profiler for performance analysis across CPU (memory bottlenecks), GPU (Xe Vector Engine (XVE) utilization issues), and NPU (memory bandwidth).
  • An overview of VTune’s native Instrumentation and Tracing Technology API (ITT API) utilities provided with the OpenVINO framework.

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Skill level: Intermediate

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Intel, the Intel logo, OpenVINO, and the OpenVINO logo are trademarks of Intel Corporation or its subsidiaries.
Intel, the Intel logo and VTune are trademarks of Intel Corporation or its subsidiaries.


 
Rupak Roy
Software Technical Consulting Engineer, Intel
Cory Levels
Software Technical Consulting Engineer, Intel

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