In the rapidly evolving landscape of large language model (LLM) development, NVIDIA Megatron Core has emerged as the foundational framework for training massive... In the...
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Enhancing Distributed Inference Performance with the NVIDIA Inference Transfer Library
Deploying large language models (LLMs) requires large-scale distributed inference, which spreads model computation and request handling across many GPUs and... Deploying large language models (LLMs)...
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Removing the Guesswork from Disaggregated Serving
Deploying and optimizing large language models (LLMs) for high-performance, cost-effective serving can be an overwhelming engineering problem. The ideal... Deploying and optimizing large language models...
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NVIDIA Blackwell Sets STAC-AI Record for LLM Inference in Finance
Large language models (LLMs) are revolutionizing the financial trading landscape by enabling sophisticated analysis of vast amounts of unstructured data to... Large language models (LLMs)...
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Controlling Floating-Point Determinism in NVIDIA CCCL
A computation is considered deterministic if multiple runs with the same input data produce the same bitwise result. While this may seem like a simple...
