AI Infrastructure

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NVIDIA Releases Dynamo v0.9.0: A Massive Infrastructure Overhaul Featuring FlashIndexer, Multi-Modal Support, and Removed NATS and ETCD

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NVIDIA has just released Dynamo v0.9.0. This is the most significant infrastructure upgrade for the distributed inference framework to date. This update simplifies how large-scale models are deployed and managed. The release focuses on removing heavy dependencies and improving how GPUs handle multi-modal data. The Great Simplification: Removing NATS and etcd The biggest change in […]

NVIDIA Releases Dynamo v0.9.0: A Massive Infrastructure Overhaul Featuring FlashIndexer, Multi-Modal Support, and Removed NATS and ETCD Read More »

NVIDIA Researchers Introduce KVTC Transform Coding Pipeline to Compress Key-Value Caches by 20x for Efficient LLM Serving

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Serving Large Language Models (LLMs) at scale is a massive engineering challenge because of Key-Value (KV) cache management. As models grow in size and reasoning capability, the KV cache footprint increases and becomes a major bottleneck for throughput and latency. For modern Transformers, this cache can occupy multiple gigabytes. NVIDIA researchers have introduced KVTC (KV

NVIDIA Researchers Introduce KVTC Transform Coding Pipeline to Compress Key-Value Caches by 20x for Efficient LLM Serving Read More »