Demystifying Google TPU SparseCore: Accelerating Recommendation Systems
How Google TPU SparseCore solves embedding lookup bottlenecks in recommender models. Learn the co-designed architecture of Trillium's SparseCores.
Tag: Infrastructure
AI Training Chip Performance: Real Scaling Data vs Marketing Hype (Blackwell to Hopper)
AI training chip performance data: analyzing real scaling from Hopper to Blackwell. 3.2x training, 50x inference gains, and why memory bandwidth matters more than FLOPs.
HBM-Aware Load Balancing with libtpu and GKE
CPU load is a trailing indicator for AI inference. Discover how to use libtpu metrics and the GKE Gateway API to build high-density, memory-aware traffic routing for TPUs.
· StrategyThe Valuation of Open Weights: The Intelligence Supply Chain
Open source models are transforming AI from a variable SaaS cost into a strategic capital asset. Discover why owning the weights is the key to Sovereign AI and a 70% reduction in long-term TCO.
Dynamic LoRA Adapters: The Anti-Monolith Strategy
Stop training dozens of specialized foundation models. Discover how dynamic Low-Rank Adaptation hot-swapping fundamentally transforms multi-tenant inference infrastructure.
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.