Michelle Horton

🌐 developer.nvidia.comSource

As context windows grow longer, moving large model weights efficiently becomes critical to performance. A common way to address this is quantization…

🌐 developer.nvidia.comSource

AI agents are quickly moving beyond chat. They inspect code, run tests, read documents, search knowledge bases, query internal systems, and operate for hours on…

🌐 developer.nvidia.comSource

GPU-accelerated query engines are often constrained by memory and I/O bandwidth. NVIDIA hardware advances—including high bandwidth memory (HBM)…

🌐 developer.nvidia.comSource

Training LLMs at massive scale brings unique infrastructure challenges, especially as jobs span thousands of GPUs and run for extended periods.

🌐 developer.nvidia.comSource

Spectrum is one of the most valuable assets in wireless communications. Over the last 30 years, telecom operators in the US have spent more than $240B to…

🌐 developer.nvidia.comSource

Agentic systems turn model reasoning into action through multi-step workflows that combine inference, tool use, code execution, retrieval, orchestration…

🌐 developer.nvidia.comSource

Molecular dynamics (MD) simulations are among the most demanding workloads in computational science. Using them, researchers can observe atomic behavior in…

🌐 developer.nvidia.comSource

There are many ways to optimize code for GPUs. In this post, you’ll learn how kernel fusion can improve memory bandwidth and reduce kernel launch overhead…

🌐 developer.nvidia.comSource

For over fifteen years, x86 CPUs have shipped with a dedicated hardware instruction for carryless multiplication. It’s a small but stubborn primitive that sits…

🌐 developer.nvidia.comSource

OpenUSD is an open, extensible framework that provides a common scene description language for physical AI. It enables teams to bring CAD data…