From API to GPU, Week 1: Understanding NVIDIA DGX Spark Environment

Short summary

First post in a 32-week series transitioning from AI API consumer to local LLM systems architect, focused on standing up and understanding the NVIDIA DGX Spark environment. Covers machine inventory via SSH, CPU vs GPU architecture differences, and why memory bandwidth matters more than raw compute for inference. Includes a runnable companion script for reproducing all environment checks on the DGX Spark.

• •32-week series from AI API consumer to local LLM architect; Week 1 covers DGX Spark environment setup
• •Explains CPU vs GPU parallelism for matrix multiplication and why memory bandwidth is the real bottleneck
• •Includes runnable inventory script for verifying machine specs, CUDA, Python, and Docker on the Spark box

Generated with AI, which can make mistakes.