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This article focuses on Graviton5, a custom silicon processor designed specifically to accelerate general-purpose and agentic AI workloads through advanced chiplet architecture and high-speed memory interconnects. While it covers broader cloud computing capabilities, the primary subject is the hardware infrastructure enabling next-generation machine learning inference and training tasks, placing it squarely within the domain of AI products and chips.
Graviton5’s improved design increases speed and energy efficiency — beyond Moore’s law
A new chiplet architecture, custom die-to-die connectivity, and support for DDR5-8800 memory and the latest PCIe gen6 interconnects improve performance by 25% for general-purpose and agentic AI workloads.
AWS Graviton processors have improved steadily across generations, with each iteration delivering advances in computational performance, price performance, energy efficiency, and memory capacity. Today, Amazon announced the general availability of the new M9g and M9gd instances of its Elastic Compute Cloud (EC2), for general-purpose workloads. These are the first Amazon products powered by Graviton5, the latest generation of Amazon’s CPU. After five generations of custom silicon and eight years of continuous investment, Graviton…
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