Related System Design
Design a Multi-Tenant LLM Inference Platform
Design a global inference service for mixed chat, coding, and long-context workloads across heterogeneous accelerators.
Design the training stack for a 100B+ parameter model across tens of thousands of accelerators.
Design a platform to train a 100B+ parameter language model on tens of thousands of accelerators, where failures are expected during every run.
Use this as one discussion aid, not a single correct answer. Your design should follow from the requirements, scale, and trade-offs you establish.
graph LR
A["Design a Fault-Tolerant Distributed LLM Training Platform"]
A --> F1["Parallelism strategy and topology mapping"]
A --> F2["Input pipeline and data quality"]
A --> F3["Checkpointing, restart, and elastic recovery"]
A --> F4["Communication, stragglers, and performance efficiency"]
A --> F5["Numerical correctness, observability, and reproducibility"]Practice drawing this system component-by-component on a live whiteboard while the interviewer probes at your target level.
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Related System Design
Design a global inference service for mixed chat, coding, and long-context workloads across heterogeneous accelerators.
Related System Design
Design scheduling and capacity management for training, research, and production inference on a large heterogeneous accelerator fleet.
Related System Design
Design the measurement, kernel, rollout, and correctness system that closes the gap between theoretical and achieved inference throughput.
Related System Design
Defend the architecture of a real project you built, its constraints, trade-offs, failures, and how you would redesign it today.