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AWS announced a tiered KV cache on SageMaker HyperPod with Curvine, extending cache to shared NVMe to reduce costs and speed up inference for large models.

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AWS SageMaker HyperPod with Curvine: Tiered KV Cache Cuts Large LLM Inference Costs

Overview

FAQ

What is tiered KV cache?

It's a technique that distributes model cache across tiers (GPU then distributed NVMe) to optimize cost and performance.

How does this benefit MENA enterprises?

It lowers the cost of running large models in regional data centers, encouraging local AI deployments.

Does this require AWS-specific infrastructure?

Yes, it relies on SageMaker HyperPod and Curvine, but it's available as a cloud service in the region.

Source: AWS Machine Learning

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