AI Infra Interviews logo
← GPU & Accelerator Architecture / 29
expertNVIDIAAnthropicOpenAI

If you could change one thing about GPU architecture for LLMs, what would it be, and what argues against it?

A proposal for more memory bandwidth needs a workload that benefits, a budget for what it costs, and a reason to abandon it. Work through a serving-specific design without assuming all LLM work has the same bottleneck.

Updated Sep 2026 · Learn how AI infrastructure works through explanations, worked examples and diagrams, then practise applying it to interview questions.

A proposal for more memory bandwidth needs a workload that benefits, a budget for what it costs, and a reason to abandon it. Work through a serving-specific design without assuming all LLM work has the same bottleneck.

The full answer is part of Premium. A free account includes more answers in each topic, but does not unlock this one.

20 answers per topic instead of 10, plus saved progress and bookmarks · no cardor unlock all 316 remaining answers · ₹2,000 / $25

Work through the numbers

Change the assumptions in a free calculator, then explain what the result establishes and what still needs measurement.

UP NEXT ON YOUR JOURNEY
FEDITOR'S NOTE

A useful proposal connects measured workload limits to one hardware change, explains what the design gives up, and names an experiment that could show the change is a poor trade.

DISCUSSION · 0

No comments yet — be the first to share your approach.