The Storage Wall: Why Your GPUs are Waiting on GCS
Buying expensive GPUs to wait on cheap storage is an operational failure. We break down the math of 'Badput' and why high-performance I/O is actually a discount.
AI Engineering
Performance over Portability? Running Local LLMs on the Asus ProArt 13
Can a thin-and-light PC handle production-level LLMs? We benchmark the Asus ProArt 13 with RTX 4060, the Ryzen AI 9 NPU, and the 8GB VRAM bottleneck.
The Agent Supervisor Pattern: Why Your Mesh Needs a Boss
Autonomous agents are prone to infinite reasoning loops and 'democratic' indecision. We explore the Supervisor pattern in LangGraph, MCP, and why orchestration beats choreography.
MoE Routing Collapse: When Your Specialists Stop Specializing
A model is only as smart as its router. We explore the physics of expert zones, the tax of token dropping, and how to keep your load balancer honest.
Visualizing All-Reduce Bandwidth: The Physics of Distributed Training
When your model doesn't fit on one GPU, you're no longer just learning coding-you're learning physics. We dive deep into the primitives of NCCL, distributed collectives, and why the interconnect is the computer.
NCCL Debugging & Tuning: NCCL_ALGO (Ring, Tree, CollNet)
NCCL debugging is critical for distributed training bottlenecks. Learn to set NCCL_DEBUG, tune the NCCL_ALGO environment variable for Ring, Tree, or CollNet, and troubleshoot GPU network failures.