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NVIDIA·Software Engineer·Technical Phone Screen·Senior

Senior
Jun 2026

Summary

Interviewed for a solutions architect role at Nvidia and got hit with a graph/ordering problem that felt more like a backend engineering screen than anything SA-adjacent. Short interview, one meaty technical question, left feeling unsure if I'd framed my answer the right way.

Questions Asked (1)

Q1

Given a directed acyclic graph representing task dependencies, how would you determine the correct execution order?

Algorithms & Data StructuresSystem Design
Author's notes

Topological sort, obviously, but I fumbled the explanation a bit.

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AI HintsAI Generated

Suggested Approach

Start by clarifying that this is a topological sorting problem on a DAG. Explain that you would use Kahn's algorithm (BFS-based) or DFS-based topological sort, and discuss how to handle edge cases like cycles and parallel execution.

Pro tip: Mention that for NVIDIA's GPU task scheduling, you'd also consider parallel execution of independent tasks and use topological sort to identify critical paths and maximize parallelism.

1. Clarify the problem

Confirm that the graph is a DAG and that we need a linear ordering of vertices such that for every directed edge u->v, u comes before v. Ask about constraints like graph size, memory, and whether parallel execution is needed.

2. Choose an algorithm

Select either Kahn's algorithm (BFS-based) or DFS-based topological sort. Discuss trade-offs: Kahn's is iterative and easy to detect cycles; DFS is recursive and can be simpler to implement.

3. Explain the algorithm

For Kahn's: compute in-degrees, enqueue nodes with in-degree 0, then repeatedly dequeue and reduce in-degrees of neighbors. For DFS: perform DFS and push nodes onto a stack after visiting all descendants.

4. Handle edge cases

Detect cycles (if not all nodes are processed, there's a cycle). Discuss disconnected graphs, multiple valid orders, and how to handle large graphs (e.g., using iterative DFS to avoid stack overflow).

5. Discuss optimizations and applications

Mention time complexity O(V+E) and space O(V+E). For NVIDIA, highlight parallel execution: independent tasks can run concurrently, and topological sort helps identify levels of parallelism.

Key Points to Mention

  • Topological sorting is only possible for DAGs; cycles indicate invalid dependencies.
  • Kahn's algorithm uses in-degrees and a queue; DFS-based uses post-order traversal.
  • Time complexity is O(V+E) for both approaches.
  • Cycle detection: if the topological sort doesn't include all nodes, a cycle exists.
  • Multiple valid topological orders may exist; any is acceptable unless additional constraints are given.
  • For parallel execution, tasks with no dependencies can run simultaneously; topological sort can be used to schedule tasks in waves.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.