What is AWS Neuron?#

AWS Neuron is a software development kit (SDK) that enables high-performance deep learning acceleration using AWS Inferentia and Trainium, AWS’s custom-designed machine learning accelerators. Neuron provides developers with the tools needed to compile, optimize, and deploy machine learning workloads on accelerated EC2 instances such as Inf1, Inf2, Trn1, Trn1n, and Trn2.

For more details, see the detailed documentation under About the AWS Neuron SDK.

Core Components#

Neuron Compiler

Optimizes machine learning models for AWS Inferentia and Trainium chips, converting models from popular frameworks into efficient executable formats.

Neuron Kernel Interface (NKI)

Provides low-level access to Neuron hardware capabilities, enabling advanced optimizations and custom operations.

Neuron Runtime

Manages model execution on Neuron devices, handling memory allocation, scheduling, and inter-chip communication for maximum throughput.

Neuron Tools

Debug and profiling utilities including:

  • Neuron Monitor for real-time performance monitoring

  • Neuron Profiler (neuron-profile) for detailed performance analysis

Neuron distributed libraries

Libraries for distributed training and inference, enabling scalable ML workloads across multiple Neuron devices.

Framework integration

Pre-integrated support for popular machine learning frameworks:

  • PyTorch

  • JAX

Supported Hardware#

AWS Inferentia

Purpose-built for high-performance inference workloads:

  • Inf1 instances - First-generation Inferentia chips

  • Inf2 instances - Second-generation with improved performance and efficiency

AWS Trainium

Designed for distributed training of large models:

  • Trn1 instances - High-performance training acceleration

  • Trn1n instances - Enhanced networking for large-scale distributed training

  • Trn2 instances - Next-generation Trainium with superior performance

  • Trn2 UltraServer - High-density Trainium servers for massive training workloads

Why use AWS Neuron?#

High Performance

Delivers up to 2.3x better price-performance compared to GPU-based instances for inference workloads.

Cost Optimization

Reduces inference costs through efficient model compilation and optimized hardware utilization.

Seamless Integration

Works with existing ML workflows through native framework support and familiar APIs.

Scalability

Supports both single-chip and multi-chip deployments for various workload sizes.

What can I use AWS Neuron for?#

Natural Language Processing

  • Large language model inference

  • Text classification and sentiment analysis

  • Machine translation

Computer Vision

  • Image classification and object detection

  • Video analysis and processing

  • Medical imaging applications

Recommendation Systems

  • Real-time personalization

  • Content recommendation engines

  • Ad targeting and optimization

Training Workloads

  • Large-scale model training on Trainium

  • Distributed training across multiple chips

  • Fine-tuning of pre-trained models

How do I get more information?#