parallel-execution

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Execute multiple independent tasks simultaneously using parallel agent coordination to maximize throughput. Use when tasks have no dependencies, results can be aggregated, and agents are available for concurrent work.

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Sourced-o-hub/rust-self-learning-memory

Added on2026-02-21

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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:

markdown

[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