hbm
AI infra interview questions tagged hbm, across every topic.
5 questions · 3 unlocked for you
Concepts behind "hbm"
The curriculum that explains the ideas these questions test.
Foundational
GPU Memory HierarchyA GPU has four places a byte can live, and they differ by a thousandfold in bandwidth: registers, shared memory on the SM, a chip-wide L2, and HBM off-chip. Almost every kernel optimization is a decision about which level a value is read from and how many times. Knowing the sizes and bandwidths for an H100 cold is what lets you say why a kernel is slow before you profile it.🧩 GPU & Accelerator Architecture
Foundational
The KV CacheThe KV cache stores each token's attention keys and values so decode never recomputes them, turning a quadratic cost into a linear one at the price of memory that grows with every token in every concurrent sequence. Its size, 128 KB per token for Llama 3.1 8B and 320 KB for 70B in bf16, is what caps concurrency and context on a given GPU, so it decides batch size, replica count and whether a model fits at all.🚀 Inference & Serving
Advanced
ECC, Row Remapping and Memory ErrorsHBM stacks flip bits, and the difference between a fleet that shrugs and one that loses a training step to corruption is error-correcting codes plus the machinery that retires bad memory before it produces a double-bit error. A single-bit error is corrected silently and counted; a double-bit error is detected, kills the process, and on Ampere and later triggers the row remapper to swap the failing row for a spare at the next reset. This page explains the codes, the remapper's states, how to read the counters as a prediction of failure, and the RMA rules a fleet applies.🩺 Fleet Reliability & Observability🔒 Premium
