Stage

Dev-tools

Nsight, CUDA tooling, editor integrations. The things that shorten the distance between an idea and its first running version.

Article №01 foundations Foundation ~6 hours spread across a week

Access First, Models Second — How I Set Up My DGX Spark for Solo AI Work

Most DGX Spark walkthroughs open with CUDA and tokens/sec. This one opens with streaming, AI-pair-programming, sandboxed agents, and browser automation — the access layer. For a solo edge builder, that interaction stack is more load-bearing than the model stack.

Upcoming dev-tools NVIDIA Nsight Systems + CUDA Toolkit planned ~4 hours including trace analysis

Tracing a NIM Request with Nsight Systems — What the 24.8 tok/s Number Hides

A planned kernel-level trace of a single NIM inference request on GB10. Where does the wall-clock time actually go — tokenization, KV-cache attention, the sampling loop, memcpy? The article turns 24.8 tokens per second into a timeline you can point at and say 'that line is the bottleneck'.