📰 Dev.to · Peter Chambers

Learn how to deploy TensorRT-LLM on NVIDIA H100 and RTX Pro 6000 GPUs. Step-by-step guide covering FP8 quantization, in-flight batching, and Triton deployment.

Learn the math behind KV cache growth, how PagedAttention cuts VRAM waste by 80%, and how to deploy vLLM with FP8 quantization.

This is a summarized guide. You can read the full, comprehensive step-by-step tutorial (including the...

Stop wasting your 80GB GPUs. Learn how to partition NVIDIA A100 and H100 cards using MIG to run multiple AI models concurrently with zero contention.

Every millisecond between a user's request and your AI model's response is a design decision—whether...

An engineering deep-dive into PCIe vs SXM architectures for NVIDIA H100 GPUs. Learn how to avoid the NVSwitch tax and optimize your AI hardware budget.

A complete guide to achieving 100% GPU efficiency for AI workloads by integrating containerd and the Kubernetes Device Plugin.

Learn how to architect and deploy a high-performance, fully private RAG pipeline using vLLM for inference and LangChain for orchestration.

As we navigate the demands of multiplayer gaming in 2026, the underlying server infrastructure has...

The NVIDIA Blackwell architecture officially marks the end of the "Hardware-Constrained" era for...

Learn how to bypass the Ubuntu 24.04 Docker Snap trap and achieve true bare-metal NVIDIA GPU passthrough for your AI and LLM workloads.