How AWS Graviton4 and Trainium2 can boost your AI performance and lower your costs

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Introduction

If you are looking for a way to improve your AI model training and inference performance, while also saving money and reducing your carbon footprint, you might want to check out the latest processors from Amazon Web Services (AWS): the Graviton4 and the Trainium2.

These processors are designed to deliver the best price performance for a broad range of cloud workloads running on Amazon Elastic Compute Cloud (Amazon EC2). They are also optimized for deep learning algorithms, supporting a wide range of data types and frameworks.

In this blog post, we will give you an overview of the features and benefits of these processors, and show you how to get started with them.


What are AWS Graviton4 and Trainium2?

AWS Graviton4 and Trainium2 are the second-generation processors that AWS purpose built for analytical and AI-focused workloads. They are based on the Arm architecture, which offers high performance, low power consumption, and scalability.

The Graviton4 is a general-purpose processor that can handle a variety of workloads, such as application servers, microservices, open-source databases, and high performance computing (HPC). It has 64 cores, 512 GB of memory, and delivers up to 2.5x the performance of the previous generation Graviton2 processor.

The Trainium2 is a machine learning (ML) accelerator that is specialized for deep learning training of large and complex models. It has 32 GB of high-bandwidth memory, delivers up to 190 TFLOPS of FP16/BF16 compute power, and features NeuronLink, an ultra-high-speed nonblocking interconnect technology. It can train AI models up to four times faster than comparable x86-based instances.

Both processors are supported by the AWS Neuron SDK, which is natively integrated with popular frameworks, such as TensorFlow and PyTorch. The Neuron SDK also supports libraries, such as Megatron-LM and PyTorch Fully Sharded Data Parallel (FSDP), for distributed model training.



What are the benefits of using AWS Graviton4 and Trainium2?

By using AWS Graviton4 and Trainium2, you can enjoy the following benefits:

  • Better price performance: AWS Graviton4 and Trainium2 offer up to 40% and 50% cost-to-train savings, respectively, over comparable x86-based instances. You can also take advantage of the AWS Free Tier, which allows you to use up to 750 hours per month of t4g.small instances powered by AWS Graviton2 processors for free until Dec 31, 2023.
  • Faster time to train: AWS Graviton4 and Trainium2 can accelerate your AI model training and inference by leveraging their high-performance cores, memory, and interconnect. You can also use AWS services, such as Amazon SageMaker, to simplify and automate your ML workflows.
  • More sustainability: AWS Graviton4 and Trainium2 use up to 60% less energy than comparable x86-based instances, which reduces your carbon footprint and helps you achieve your sustainability goals.


How to get started with AWS Graviton4 and Trainium2?

To get started with AWS Graviton4 and Trainium2, you need to follow these steps:

  • Step 1: Choose the AWS Graviton4 or Trainium2 based instance that best meets your needs. You can find the list of available instances here for Graviton4 and here for Trainium2.
  • Step 2: Launch your instance using the AWS Management Console, AWS Command Line Interface (CLI), or AWS SDKs. You can also use AWS CloudFormation templates or AWS Marketplace AMIs to automate the process.
  • Step 3: Install the AWS Neuron SDK on your instance. You can use the AWS Deep Learning AMIs (DLAMI) or AWS Deep Learning Containers, which come preconfigured with the Neuron SDK and the frameworks and libraries that you need.
  • Step 4: Modify your code to use the Neuron SDK APIs and optimize your model for the Graviton4 or Trainium2 processor. You can find the documentation and examples here for Graviton4 and [here] for Trainium2.
  • Step 5: Run your code and enjoy the improved performance and cost savings.

Conclusion

AWS Graviton4 and Trainium2 are the latest processors from AWS that can help you boost your AI performance and lower your costs. They are also optimized for deep learning algorithms, supporting a wide range of data types and frameworks. By using these processors, you can also reduce your carbon footprint and contribute to a more sustainable future.

If you want to learn more about AWS Graviton4 and Trainium2, you can visit the official website or watch the Invent keynote where they were announced. You can also check out the customer stories and partner solutions that showcase how these processors are being used in various industries and applications.

We hope you found this blog post helpful and informative. If you have any questions or feedback, please feel free to leave a comment below. 

Thank you for reading and happy coding! 😊






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