NVIDIA CUDA, Triton & Kernel Engineering interview questions

Map a non-divisible array onto blocks, guard the final 189 threads, and separate kernel traffic from host transfers without inventing measured timings.

Count warp sectors for contiguous, strided and masked accesses, then use cache and timing evidence to decide whether changing the mapping helps.

Build a mask-aware classifier that counts complete byte intervals, separates duplicate lane demand from distinct bytes, and streams trace summaries.

Derive the bank mapping before and after padding, trace a fixed-tile kernel, and measure whether the saved conflict outweighs other resource costs.

Follow an accumulator across K tiles, count reuse at each memory level, and decide whether a tile improves measured GEMM performance.

Derive resident-block limits and distinguish resident warps from ready work before trading registers for more occupancy.

Compare the mechanisms in FlashAttention versions 1, 2 and 3: IO savings, work partitioning, asynchronous dependencies and FP8 accuracy.

Separate cache activity from DRAM traffic, check the access width and active lanes, and use a controlled layout change to test a profiler hypothesis. A few percentages cannot predict the fixed kernel’s runtime.

Build a reduction with a checked tail, one partial result per block and a final combine. Count the input bytes, then investigate the instructions, synchronization and numerical behavior that a bandwidth estimate leaves out.

Trace how a shared-memory tile turns coalesced input rows into coalesced output rows. Then separate global sector footprints, shared-bank conflicts and measured bandwidth, including the cost of handling edge tiles.

Use a timeline to establish launch overhead, then trace what graph replay changes. Stable buffers, page-table updates, capture-safe operations and batch buckets determine whether the serving engine can use it safely.

Use cuBLAS or cuBLASLt when its supported operation fits. CUTLASS exposes kernel building blocks for custom layouts, fusion and scheduling, but each choice needs a whole-operation benchmark and an ownership plan.

An asynchronous call returns early, but the timeline still shows copies and kernels taking turns. Derive the pipeline's fill and drain costs, then check dependencies, buffers and hardware before expecting overlap.

Watch a low-precision sum stop changing and a small weight update round away. Separate storage precision, accumulation, optimizer state and dynamic range before choosing a mixed-precision training policy.

Derive when operand scales can be applied after a dot product and when they must follow its K blocks. Separate integer zero points, floating-point range, scale granularity and accumulator behavior.

Choose between local candidates, radix selection and sorting from k and the required output. A tested FP32 reference makes ties, signed zero, NaNs and threshold selection explicit.

A few extra live values can change register allocation, residency, generated instructions or spills. Compare compiler evidence with runtime behavior before attributing a 30% slowdown to any one of them.

Follow the running maximum and weighted sum across attention tiles, with executable arithmetic and an honest memory-traffic comparison.

Trace stable row normalization, handle independent strides and fully masked inputs, then separate fusion traffic from measured speed.

Follow intermediate tensors through separate and fused stages, calculate the traffic and whole-block bounds, and check spills and numerical behavior.

Build a numerical reference, count the traffic and investigate a row-wise fused kernel. Separate bandwidth lower bounds from measured performance.

Compute MFU with a stated work model, then follow the training step’s critical path across input, host dispatch, computation and communication. Rank experiments by exposed time instead of assigning universal gains to fixes.

Verify a drafted prefix without biasing the target distribution, then roll back rejected KV state. A six-token prefix exposes the off-by-one: nine committed tokens can have only eight valid KV entries.