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