6 posts
On-premise deployment experience: a field note where timeline, hardware procurement, network constraints and update burden differ from the plan. With a readiness checklist.
What is a GPU? A GPU is a processor that performs parallel computation with thousands of cores and forms the heart of AI hardware. VRAM, CPU vs GPU, training vs inference in this guide.
How to build on-premise AI infrastructure? Hardware, model serving, scaling, monitoring, updates and the real operational burden — an enterprise decision guide.
How to size hardware for an on-premise LLM: a practical guide to VRAM math, quantization, concurrent users, GPU count and server sizing for enterprise deployments.
On-prem LLM deployment guide: hardware requirements, GPU and VRAM, quantization savings, the serving stack, and on-prem vs API total cost of ownership calculation.
What is a GPU? A GPU (Graphics Processing Unit) is hardware designed for parallel processing that runs the same operation across massive data simultaneously with thousands of small cores. This guide: a clear definition, how a GPU works, the difference from a CPU, VRAM, CUDA, its role as AI hardware, examples, limits, and FAQs.