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 / ParallelExample: 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