At its re:Invent conference in Las Vegas, Amazon Web Services (AWS) announced the next generation of two AWS-designed chip families—AWS Graviton4 and AWS Trainium2. These new chips deliver advancements in price performance and energy efficiency for a broad range of customer workloads, including machine learning (ML) training and generative artificial intelligence (AI) applications.
Graviton4: The Most Powerful and Energy-Efficient AWS Processor
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Graviton4 is the most powerful and energy-efficient AWS processor to date. It provides up to 30% better compute performance, 50% more cores, and 75% more memory bandwidth than current generation Graviton3 processors. Graviton4 also raises the bar on security by fully encrypting all high-speed physical hardware interfaces.
Graviton4 will be available in memory-optimised Amazon EC2 R8g instances, enabling customers to improve the execution of their high-performance databases, in-memory caches, and big data analytics workloads. R8g instances offer larger instance sizes with up to 3x more vCPUs and 3x more memory than current generation R7g instances. This allows customers to process larger amounts of data, scale their workloads, improve time-to-results, and lower their total cost of ownership. Graviton4-powered R8g instances are available today in preview, with general availability planned in the coming months.
Trainium2: Designed for the Highest Performance AI Model Training
Trainium2 is designed to deliver up to 4x faster training performance and 3x more memory capacity compared to first-generation Trainium chips, while improving energy efficiency (performance/watt) up to 2x. Trainium2 will be available in Amazon EC2 Trn2 instances, containing 16 Trainium chips in a single instance. Trn2 instances are intended to enable customers to scale up to 100,000 Trainium2 chips in next generation EC2 UltraClusters, interconnected with AWS Elastic Fabric Adapter (EFA) petabit-scale networking, delivering up to 65 exaflops of compute and giving customers on-demand access to supercomputer-class performance. With this level of scale, customers can train a 300-billion parameter LLM in weeks versus months.
What This Means for Customers
The announcement of new AWS chips is significant because it will provide customers with more powerful and energy-efficient options for running their workloads in the cloud. This will help customers to improve performance, reduce costs, and innovate faster.
Here are some of the benefits that customers can expect from Graviton4 and Trainium2:
- Improved performance for a broad range of workloads
- Reduced costs
- Increased energy efficiency
- Scalability to meet the demands of the most challenging workloads
