#Memory Bandwidth

Articles about Memory Bandwidth — exploring patterns, best practices, and real-world implementations in production systems.

1 post tagged with memory bandwidth. ← All posts

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Pratik Dhanave · ·5 min read

The Memory Hierarchy — Why Bandwidth Rules Inference

Post 1 ended on a reversal: GPUs are fast at arithmetic, but arithmetic is rarely the bottleneck — moving data is. This post makes that concrete by walking the GPU's memory hierarchy, from the tiny ultra-fast registers next to the compute units down to the big slow memory that holds the model's weights. Once you see the orders-of-magnitude gaps between these levels, every performance decision in LLM inference starts to make sense.

The GPU memory hierarchy from registers to HBM, the difference between capacity and bandwidth limits, and the defining fact of LLM generation: it's memory-bandwidth-bound because every token reads the whole model from HBM — which is why batching and quantization work.

#GPU#Memory Bandwidth#Inference#Performance#LLMs

All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.