← NVIDIA Interview Insights

NVIDIA·Software Engineer·Onsite - System Design / Architecture·Senior

Senior
Jul 2026

Summary

NVIDIA system design round for a software engineering role. The whole thing was one big question about designing a DAG-based IR for a graphics testing workflow, and it went deep fast. Definitely not a question you can wing.

Questions Asked (1)

Q1

Design an intermediate representation (IR) for a graphics testing workflow modeled as a directed acyclic graph. Define the node and edge types, metadata structure, and how you'd model side effects. Then explain how you'd compile that IR into an executable plan with caching, incremental rebuilds, and deterministic ordering. Also address versioning and schema evolution.

System DesignData ModelingTechnical Trade-offs
Author's notes

This one is basically four questions stitched together and they expect you to treat it as one coherent design.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying the requirements and constraints of the graphics testing workflow, then define the IR with nodes, edges, metadata, and side-effect modeling. Next, explain the compilation process into an executable plan, covering caching, incremental rebuilds, and deterministic ordering. Finally, discuss versioning and schema evolution strategies to ensure long-term maintainability.

Pro tip: Emphasize determinism and reproducibility early, as they are critical for testing workflows and demonstrate an understanding of production-grade systems. Also, mention how your design balances flexibility with performance, a key trade-off in system design.

1. Clarify Requirements and Constraints

Ask questions to understand the scale, types of graphics tests, performance needs, and integration points. This ensures your design is grounded in real-world constraints.

2. Define the IR Structure

Specify node types (e.g., test, setup, teardown, assertion) and edge types (e.g., data dependency, control dependency). Include metadata such as test parameters, expected outputs, and resource requirements.

3. Model Side Effects and Execution Semantics

Identify side effects (e.g., file I/O, GPU state changes) and model them explicitly, perhaps with special nodes or edge annotations. Define execution semantics to handle ordering and isolation.

4. Design the Compilation and Execution Plan

Describe how to compile the IR into an executable plan: topological sorting for deterministic ordering, caching based on node hashes, and incremental rebuilds by tracking dirty nodes.

5. Address Versioning and Schema Evolution

Propose a versioning scheme for the IR (e.g., semantic versioning) and strategies for backward/forward compatibility, such as optional fields, versioned nodes, and migration tools.

Key Points to Mention

  • Node and edge types with clear semantics (e.g., data vs. control dependencies)
  • Metadata structure including test parameters, expected results, and resource specs
  • Explicit modeling of side effects to ensure correct ordering and isolation
  • Caching strategy using content-addressable hashes of nodes and dependencies
  • Incremental rebuilds via dirty tracking and dependency graph analysis
  • Deterministic ordering through topological sort with tie-breaking rules
  • Versioning approach (e.g., semantic versioning) and schema evolution techniques

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