TOPIC 1

Build AI/ML Apps

Optimize ML inference and training performance on Arm Neoverse, as well as best practices for ML inference using PyTorch 2.0, and more.

 

  • Google Axion processors, powered by Arm Neoverse V2 CPU platform, is now generally available to the public on Google Cloud. The first Axion based cloud VMs, C4A, delivers giant leaps in performance for CPU-based AI inferencing and general-purpose cloud workloads.

Best Practices to Optimize ML Performance on AWS Graviton

  • : A series of blogs covering how to improve performance and reduce costs for ML inference, as well as NN training, and more.
  • :
    A case study that compares the ML inference performance with x86, achieving 1.8x faster inference workloads.
  • , XGBoost is used to solve regression and classification problems in data science using machine learning. LightGBM is another open-source GDBT-based tool developed by Microsoft, mostly known for more efficient training compared to XGBoost.

  • In this blog post, we focus on Alibaba Elastic Cloud Service (ECS) powered by Yitian 710 to test and compare the performance of deep learning inference.

  • Example tutorial showcasing how to achieve the best inference performance with bfloat16 kernels, and the right back-end selection.

  • Learn how to build and use Docker images for TensorFlow and PyTorch for Arm.
TOPIC 2

Build GenAI Apps

Learn the capabilities of Arm Neoverse CPUs running LLMs and SLMs, and accelerate Hugging Face (HF) models on Arm.

 

LLM Performance on Arm Neoverse

  • Demoing LLM inference with .
  • Learn about the capabilities of in running LLMs, showcasing the key advantages compared to other CPU-based server platforms.
  • : this blog post explores the capabilities of Arm Neoverse N2 based Alibaba Yitian710 CPUs running industry-standard Large Language Models (LLMs), such as LLaMa3 and Qwen1.5, with flexibility and scalability.

LLM Chatbot on Arm

  • Discover how you can run an using KleidiAI on Arm-based servers.
  • Learn how to run an using KleidiAI on Arm-based servers.

  • Overview of the usability of SLMs in a more efficient and sustainable way, requiring fewer resources, and being easier to customize and control compared to LLMs.

  • Learn about the key features in Arm Neoverse CPUs for ML, with a Sentiment Analysis use case.

Accelerate and Deploy NLP Models from HF

  • Learn how to 
  • A getting started guide on  using PyTorch on Arm-based servers.
TOPIC 3

Accelerate GenAI, AI, and ML

Accelerate your AI/ML framework, tools, and cloud services with open-source Arm libraries and optimized Arm SIMD code.

 

Accelerating Pytorch Inference

  • technology on Arm Neoverse.
  • Graviton processors: A collaboration between AWS, Arm, and Meta, increasing performance up to 3.5 times compared to the previous PyTorch release, and more.

Arm Compute Library (ACL)

  • ACL is an open-source fully featured library, with a collection of low-level ML functions optimized for Arm Neoverse and other Arm architectures.

Arm Kleidi

  • Arm Kleidi open-source libraries are a lighter weight performance library (compared to ACL) for accelerating AI and ML workloads and frameworks.
  • A Getting started guide on how to accelerate GenAI workloads using .
  • The library is designed for image processing and integrates into any CV framework to enable best performance for CV workloads on Arm.
  • Blog presenting how on Arm Neoverse N2. 

Arm SIMD code

  • Optimize your AI/ML workloads with Arm SIMD code, either in assembly or using Arm Intrinsics in C/C++, to leverage huge performance gains.

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Community Support

Learn from the Community

Talk directly to Arm expert, Zach Lasiuk, and the broader Arm community in the servers and cloud computing today.

Zach Lasiuk

Zach helps software devs do their best work on Arm, specializing in cloud migration and GenAI apps. He is an XTC judge in Deep Tech and AI Ethics.

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