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Group Anagrams at NVIDIA — Interview Guide

The problem at NVIDIA

Given an array of strings, group the anagrams together. An anagram group contains strings that are rearrangements of the same letters.

NVIDIA uses this problem to assess systems, performance, and parallel thinking. Expect NVIDIA-specific follow-ups that tie the solution back to production reasoning and the company's engineering bar.

Key concepts

Sorting each string gives a canonical key — O(k log k) per string.
A 26-character count tuple is a key in O(k) per string and is faster for long strings.
Both produce the same groups; the count key wins when strings are long.

Approach

import collections
def group_anagrams(strs):
    groups = collections.defaultdict(list)
    for s in strs:
        key = [0] * 26
        for c in s:
            key[ord(c) - 97] += 1
        groups[tuple(key)].append(s)
    return list(groups.values())

What NVIDIA looks for

Low-level fluency — memory, caches, concurrency, SIMD.
Performance mindset — profile, optimize, and reason about bottlenecks.
Domain depth for the team (graphics, ML infra, autonomous systems).
Collaboration across hardware and software boundaries.

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