Hardware-Software Co-Design

Stop Throwing Compute at Your LLMs. You’re Solving the Wrong Problem.

📅 August 14, 2026 📂 AI & Machine Learning

You’ve probably noticed that training your LLM is painfully slow, and throwing more compute at it just burns cash. The abstractions that make AI portable are the exact same ones hiding massive hardware inefficiencies. If you’re optimizing a GPT-2-class model on a single GPU, you’re learning the wrong lessons for scale.

The MoE Training Bottleneck That 99% of Engineers Miss — and How to Bypass It Entirely

📅 August 5, 2026 📂 Systems & Hardware

Most MoE training bottlenecks come from treating the network as a communication layer. But a new hardware-software co-design approach treats remote servers as pooled memory, making the cluster behave like a single machine. This eliminates NCCL stalls entirely, boosting GPU utilization. The fix isn’t faster networking — it’s a new abstraction.

AI Infrastructure Bottleneck Distributed Systems GPU Hardware-Software Co-Design MoE NCCL