Host CPU, PCIe and Storage: The Bottlenecks Around the Accelerator
Why a fast accelerator can sit idle: how host CPU, PCIe links, storage and data loading limit AI workloads, and how to find the bottleneck.
AI Chips & Accelerators
AI Hardware Architecture
AI Hardware Architecture guides, comparisons and explainers from AIChipNexus.
Interconnects and Multi-Accelerator Scaling Explained
How accelerators are linked inside servers and across clusters, why communication limits scaling, and what to check before buying multi-device systems.
KV Cache and Batching: Why LLM Inference Stresses Hardware Differently
How the KV cache and batching change memory and compute demands during LLM inference, and what that means for choosing and sizing accelerators.
Memory Bandwidth and Capacity: The Bottleneck Behind Most AI Hardware Choices
Why memory capacity and bandwidth often limit AI performance more than raw compute, and how to reason about both when evaluating accelerators.