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This is a hard difficulty System Design question, commonly asked during Take-home Project rounds at NVIDIA.

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This question is commonly asked for Software Engineer candidates at NVIDIA during technical interviews.

Build a Jenkins CI for graphics tests | NVIDIA Interview Question

Quick Overview

This question evaluates a candidate's ability in CI/CD and system design for GPU-dependent test orchestration, specifically Jenkins pipeline design, hardware/driver matrix scheduling, test sharding and retries, artifact provenance, release gating, and safe driver rollout.

Take‑Home: Design a Jenkins Pipeline for GPU Graphics Test Matrix

Context

You need to design a Jenkins-based CI/CD system that builds a graphics application/library, deploys it to GPU-equipped test hosts, and runs automated graphics tests across a matrix of GPU hardware and driver versions. The system must scale to dozens of machines and be reliable in the face of flaky tests and occasional host/driver problems.

Assume:

You have a fleet of bare‑metal agents with different GPU models and multiple driver versions.
Tests are GPU‑dependent, may use headless EGL or virtual displays, and produce JUnit XML, logs, and performance metrics.
Builds can run on CPU-only builders; tests require GPUs.

Task

Propose a Jenkins pipeline design and describe how you will handle:

Job orchestration and pipeline-as-code (Jenkinsfile, shared libraries).
Parallelization across a hardware/driver matrix without oversubscribing GPUs.
Artifact management (builds, logs, test results, metrics) and provenance.
Test sharding (balanced by historical duration) and re-run of failed tests.
Retry policies for transient infra vs. test-level flakiness.
Quarantining flaky tests so they don’t gate merges, while still being exercised.
Notifications and PR status reporting with a clear matrix summary.
Promotion gates from CI → pre-prod → prod (quality and performance thresholds, manual approval when needed).
Safe driver updates and rollback across the fleet (canaries, labels, blue/green, health checks).

Deliver:

A written design with rationale and guardrails.
A Jenkinsfile sketch that demonstrates the matrix fan-out, sharding, retries, artifact handling, and gating.
Any minimal assumptions you make explicit.

Quick Overview

Context

Assume:

You have a fleet of bare‑metal agents with different GPU models and multiple driver versions.

Tests are GPU‑dependent, may use headless EGL or virtual displays, and produce JUnit XML, logs, and performance metrics.

Builds can run on CPU-only builders; tests require GPUs.

Task

Propose a Jenkins pipeline design and describe how you will handle:

Job orchestration and pipeline-as-code (Jenkinsfile, shared libraries).

Parallelization across a hardware/driver matrix without oversubscribing GPUs.

Artifact management (builds, logs, test results, metrics) and provenance.

Test sharding (balanced by historical duration) and re-run of failed tests.

Retry policies for transient infra vs. test-level flakiness.

Quarantining flaky tests so they don’t gate merges, while still being exercised.

Notifications and PR status reporting with a clear matrix summary.

Promotion gates from CI → pre-prod → prod (quality and performance thresholds, manual approval when needed).

Safe driver updates and rollback across the fleet (canaries, labels, blue/green, health checks).

Deliver:

A written design with rationale and guardrails.

A Jenkinsfile sketch that demonstrates the matrix fan-out, sharding, retries, artifact handling, and gating.

Any minimal assumptions you make explicit.

Build a Jenkins CI for graphics tests

Quick Overview

Take‑Home: Design a Jenkins Pipeline for GPU Graphics Test Matrix

Context

Task

Solution

Comments (0)

Build a Jenkins CI for graphics tests

Quick Overview

Take‑Home: Design a Jenkins Pipeline for GPU Graphics Test Matrix

Context

Task

Solution

Comments (0)