Parallel Execution

Execute multiple independent tasks simultaneously to maximize throughput and minimize total execution time.

When to Use

• Multiple independent tasks (no dependencies)
• Tasks benefit from concurrent execution
• Maximizing throughput is priority
• Available agents for parallel work
• Results can be aggregated after completion

Core Concepts

Independence

Tasks are independent when:

• ✓ No data dependencies
• ✓ No resource conflicts
• ✓ No ordering requirements
• ✓ Failures are isolated

Concurrency

Critical: Use single message with multiple Task tool calls:

[Task tool] → Agent A
[Task tool] → Agent B
[Task tool] → Agent C

All start simultaneously.

Execution Patterns

Pattern	Description	Example
Homogeneous	Same agent, different inputs	Test 3 modules
Heterogeneous	Different agents, related task	Review + Test + Profile
Parallel + Convergence	Parallel → Synthesize	Profile + Analyze → Root cause

Synchronization Strategies

• Wait for All: Proceed when ALL complete
• Wait for Any: Early termination on first success
• Threshold: Proceed when N of M complete

Performance

Sequential: T1 + T2 + T3
Parallel: max(T1, T2, T3)
Speedup = Sequential / Parallel

Example: 3 tasks (10+15+8 min) → Parallel (15 min) = 2.2x faster

Best Practices

✓ Verify independence before parallelizing ✓ Use single message with multiple Task calls ✓ Balance workload across agents ✓ Handle failures gracefully

✗ Don't parallelize dependent tasks ✗ Don't send sequential messages