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Optimize machines for distributed merging cost

Last updated: Mar 29, 2026

Quick Overview

This question evaluates a candidate's ability to perform asymptotic performance analysis and reason about scalability trade-offs between parallel computation and aggregate merge costs.

  • medium
  • Kneron
  • System Design
  • Software Engineer

Optimize machines for distributed merging cost

Company: Kneron

Role: Software Engineer

Category: System Design

Difficulty: medium

Interview Round: Take-home Project

In a distributed computation, processing the entire dataset on one machine takes O(n) time. If the data is evenly partitioned across k machines, the per‑machine compute time becomes O(n/k). Merging the partial results from the k machines takes O(k^ 2) time. Assuming negligible other overheads, which value of k approximately minimizes the total runtime O(n/k + k^ 2)? Pick ONE option: A) around 10 B) around log2 n C) around square root of n D) around n/2

Quick Answer: This question evaluates a candidate's ability to perform asymptotic performance analysis and reason about scalability trade-offs between parallel computation and aggregate merge costs.

Kneron logo
Kneron
Jul 26, 2025, 12:00 AM
Software Engineer
Take-home Project
System Design
1
0

Optimize k to Minimize Distributed Runtime

Context

You are splitting a dataset of size n across k identical machines.

  • Per-machine compute (with even partitioning): O(n/k)
  • Merge cost of the k partial results: O(k^2)
  • Other overheads are negligible

Total runtime: T(k) = O(n/k + k^2)

Question

Which value of k approximately minimizes the total runtime? Pick ONE option:

  • A) around 10
  • B) around log₂ n
  • C) around square root of n
  • D) around n/2

Solution

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