Skip to content

4. Parallelization

Mini-Project: Editorial Review Board

Multiple specialist reviewers (tone, facts, grammar) analyze a document in parallel, and their feedback is merged into a unified editorial report.

View on GitHub


Description

Parallelization fans out a task to multiple LLM calls that run concurrently, then aggregates their results. There are two main variants:

  • Sectioning: Breaking a task into independent subtasks that run in parallel
  • Voting: Running the same task multiple times to get diverse outputs for consensus

When to Use

  • Tasks with independent subtasks that don't depend on each other
  • When you need multiple perspectives on the same problem (voting/ensemble)
  • Reducing wall-clock time for multi-part analysis
  • Quality assurance through redundant evaluation

Benefits

Benefit Description
Speed Concurrent execution reduces total time
Quality Multiple perspectives catch more issues
Robustness Voting reduces individual LLM errors
Throughput Process more work in the same time window

Architecture Diagram

flowchart TD
    A[User Input] --> B[Fan-Out / Split]
    B --> C[Agent 1: Analyze Tone]
    B --> D[Agent 2: Check Facts]
    B --> E[Agent 3: Review Grammar]
    C --> F[Aggregator / Merge]
    D --> F
    E --> F
    F --> G[Combined Output]

    style A fill:#4CAF50,color:#fff
    style B fill:#FF9800,color:#fff
    style C fill:#2196F3,color:#fff
    style D fill:#9C27B0,color:#fff
    style E fill:#00BCD4,color:#fff
    style F fill:#FF9800,color:#fff
    style G fill:#4CAF50,color:#fff