5 posts tagged gpu-infrastructure from Omnissiah Systems.
How pipeline bubbles form in multi-stage model inference, how to measure them precisely, and what scheduling changes actually reduce their cost.
A field guide to the failure modes that emerge when you scale tensor parallelism across GPU ranks: communication bottlenecks, numerical drift, and load imbalance.
A practical guide to KV cache eviction policies in distributed LLM inference: what triggers eviction, how it degrades latency, and how to tune against it.
How misconfigured gradient accumulation silently corrupts large model training runs, and the specific checks you need to catch it before loss curves lie to you.