BMAD-METHOD/.claude/orchestrator/parallel-execution-engine.md

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# Parallel Execution Engine - Performance Optimization System
## System Overview
The Parallel Execution Engine optimizes workflow performance by executing independent agents simultaneously, managing resource allocation, and coordinating synchronization points for maximum efficiency.
## Parallel Execution Architecture
### Dependency Analysis Engine
```yaml
dependency_analyzer:
analysis_scope: "full_workflow_dependency_graph"
dependency_types:
data_dependency:
description: "Agent B requires structured data from Agent A"
example: "pm requires analyst.project_brief.structured_data"
blocking: true
context_dependency:
description: "Agent B benefits from Agent A's context but can work without it"
example: "ux_expert can use architect.technology_stack if available"
blocking: false
validation_dependency:
description: "Agent B needs Agent A for output validation"
example: "architect validates pm's technical requirements"
blocking: false # Can be done post-completion
resource_dependency:
description: "Agents compete for the same computational resources"
example: "multiple agents using same template engine"
blocking: false # Managed by resource allocator
dependency_graph_generation:
algorithm: "topological_sort_with_parallel_identification"
optimization: "minimize_critical_path_length"
output: "execution_groups_with_parallel_opportunities"
```
### Execution Group Definition
```yaml
execution_groups:
group_1_foundation:
agents: ["analyst"]
dependencies: []
parallel_capable: false
estimated_duration: "3-5_minutes"
resource_requirements:
cpu: "medium"
memory: "low"
context_access: "write_only"
group_2_requirements:
agents: ["pm"]
dependencies: ["analyst.completion"]
parallel_capable: false # Single critical path
estimated_duration: "4-6_minutes"
resource_requirements:
cpu: "high"
memory: "medium"
context_access: "read_analyst_write_pm"
group_3_design_architecture:
agents: ["ux_expert", "architect"]
dependencies: ["pm.completion"]
parallel_capable: true # Key optimization opportunity
synchronization: "barrier_sync"
estimated_duration: "6-8_minutes"
agent_specifications:
ux_expert:
inputs: ["pm.user_stories", "pm.user_personas", "analyst.target_users"]
outputs: ["ui_spec", "user_journeys", "component_specifications"]
resource_requirements:
cpu: "medium"
memory: "medium"
context_access: "read_multiple_write_ux"
architect:
inputs: ["pm.functional_requirements", "pm.non_functional_requirements", "analyst.technical_constraints"]
outputs: ["system_architecture", "technology_stack", "api_specifications"]
resource_requirements:
cpu: "high"
memory: "high"
context_access: "read_multiple_write_architect"
synchronization_strategy:
type: "smart_barrier"
timeout: "10_minutes"
partial_failure_handling: "continue_with_available_results"
cross_validation: "post_completion_validation"
group_4_implementation:
agents: ["developer"]
dependencies: ["ux_expert.completion", "architect.completion"]
parallel_capable: false
estimated_duration: "8-12_minutes"
resource_requirements:
cpu: "very_high"
memory: "high"
context_access: "read_multiple_write_developer"
group_5_quality:
agents: ["qa"]
dependencies: ["developer.completion"]
parallel_capable: false
estimated_duration: "4-6_minutes"
resource_requirements:
cpu: "medium"
memory: "medium"
context_access: "read_all_write_qa"
```
### Resource Management System
```yaml
resource_manager:
resource_pool:
computational:
total_cpu_units: 100
total_memory_units: 100
concurrent_agent_limit: 3
context_store:
concurrent_readers: 5
concurrent_writers: 1
lock_timeout: 30 # seconds
template_engine:
concurrent_renders: 3
cache_size: "50MB"
render_timeout: 120 # seconds
allocation_strategy:
algorithm: "priority_based_fair_sharing"
priorities:
critical_path_agents: 10
parallel_group_agents: 7
validation_agents: 5
resource_sharing:
cpu_oversubscription: 1.2 # Allow 120% allocation
memory_strict: true # No oversubscription
context_queuing: true
load_balancing:
agent_assignment:
strategy: "least_loaded_instance"
health_check: "response_time_based"
failover: "automatic_reassignment"
resource_monitoring:
metrics: ["cpu_usage", "memory_usage", "response_time", "queue_depth"]
sampling_interval: 10 # seconds
alert_thresholds:
cpu_usage: 90
memory_usage: 85
response_time: 180 # seconds
queue_depth: 3
```
## Parallel Coordination Protocol
### Smart Barrier Synchronization
```yaml
barrier_synchronization:
implementation: "smart_barrier_with_partial_results"
phases:
phase_1_initiation:
- start_all_parallel_agents_simultaneously
- establish_shared_context_locks
- begin_progress_monitoring
phase_2_execution_monitoring:
- track_individual_agent_progress
- monitor_resource_utilization
- detect_potential_conflicts_early
- provide_progress_updates
phase_3_completion_detection:
- wait_for_all_agents_OR_timeout
- collect_completed_results
- assess_partial_completion_viability
- make_continuation_decision
phase_4_synchronization:
- merge_parallel_results
- resolve_any_conflicts
- validate_cross_agent_consistency
- prepare_context_for_next_group
timeout_handling:
default_timeout: "10_minutes"
timeout_strategies:
continue_with_partial:
condition: "at_least_one_agent_completed_successfully"
action: "use_completed_results_fill_gaps_with_defaults"
quality_impact: "medium"
extend_timeout:
condition: "agents_making_progress_but_need_more_time"
extension: "5_minutes_maximum"
max_extensions: 1
abort_and_fallback:
condition: "no_agents_completing_OR_critical_errors"
action: "fall_back_to_sequential_execution"
notification: "alert_system_administrators"
```
### Context Conflict Resolution
```yaml
context_conflicts:
conflict_types:
write_write_conflict:
description: "Multiple agents trying to write to same context location"
resolution: "first_writer_wins_with_merge_opportunity"
example: "both ux_expert and architect updating user_requirements"
read_write_conflict:
description: "Agent reading while another agent writing"
resolution: "consistent_snapshot_isolation"
example: "pm reading analyst_data while analyst updating"
consistency_conflict:
description: "Parallel agents producing inconsistent outputs"
resolution: "post_completion_conflict_detection_and_resolution"
example: "ux_expert specifies mobile_first while architect assumes desktop_primary"
resolution_mechanisms:
optimistic_concurrency:
strategy: "allow_parallel_execution_detect_conflicts_later"
conflict_detection: "content_hash_comparison"
resolution: "three_way_merge_with_validation"
context_versioning:
strategy: "version_all_context_changes"
merge_strategy: "semantic_merge_where_possible"
fallback: "manual_conflict_resolution"
conflict_prevention:
strategy: "pre_allocate_context_ownership"
ownership_rules:
analyst: ["project_metadata", "problem_analysis", "user_research"]
pm: ["requirements", "user_stories", "acceptance_criteria"]
architect: ["technical_architecture", "system_design", "api_specs"]
ux_expert: ["user_experience", "ui_specifications", "design_system"]
```
## Performance Optimization Features
### Intelligent Caching System
```yaml
caching_system:
cache_levels:
agent_output_cache:
scope: "completed_agent_outputs"
key_strategy: "content_hash_based"
ttl: "session_lifetime"
size_limit: "100MB"
template_render_cache:
scope: "rendered_template_outputs"
key_strategy: "template_id_plus_variable_hash"
ttl: "1_hour"
size_limit: "50MB"
context_snapshot_cache:
scope: "context_state_at_major_milestones"
key_strategy: "workflow_step_plus_content_hash"
ttl: "session_lifetime"
size_limit: "200MB"
cache_optimization:
prefetching:
strategy: "predict_next_likely_agent_needs"
prefetch_templates: true
prefetch_context: true
compression:
algorithm: "lz4_fast_compression"
compression_threshold: "10KB"
eviction:
policy: "lru_with_priority_boosting"
priority_factors: ["access_frequency", "computation_cost", "cache_hit_ratio"]
```
### Performance Monitoring
```yaml
performance_monitoring:
metrics_collection:
execution_metrics:
- total_workflow_time
- individual_agent_execution_time
- parallel_efficiency_ratio
- context_lock_wait_time
- resource_utilization_percentage
quality_metrics:
- output_quality_scores
- validation_failure_rate
- context_conflict_frequency
- retry_rate
system_metrics:
- memory_usage_peak
- cpu_utilization_average
- cache_hit_ratios
- network_latency_impact
performance_optimization:
adaptive_resource_allocation:
trigger: "performance_below_threshold"
actions:
- increase_cpu_allocation
- adjust_parallel_group_sizes
- modify_timeout_values
- enable_aggressive_caching
bottleneck_detection:
algorithm: "critical_path_analysis"
automatic_optimization:
- reorder_non_critical_operations
- increase_parallelization_opportunities
- optimize_context_access_patterns
```
## Integration with Workflow Engine
### Enhanced Workflow Execution
```yaml
# Enhanced workflow step definition with parallel capabilities
enhanced_workflow_step:
id: "step_3_parallel_design"
name: "Parallel Design & Architecture"
type: "parallel_group"
parallel_configuration:
execution_mode: "truly_parallel"
resource_isolation: false # Allow resource sharing
context_sharing: "read_only_shared_write_isolated"
agents:
- id: "ux_expert_parallel"
agent: "ux_expert"
priority: 7
timeout: "8_minutes"
context_requirements:
read: ["pm.user_stories", "analyst.target_users"]
write: ["ux_outputs"]
resource_requirements:
cpu: 30 # units
memory: 25 # units
- id: "architect_parallel"
agent: "architect"
priority: 8 # Slightly higher priority
timeout: "10_minutes"
context_requirements:
read: ["pm.requirements", "analyst.technical_constraints"]
write: ["architecture_outputs"]
resource_requirements:
cpu: 40 # units
memory: 35 # units
synchronization:
barrier_type: "smart_barrier"
success_criteria: "at_least_one_agent_succeeds"
failure_criteria: "all_agents_fail_or_timeout"
cross_validation:
enabled: true
validation_agents: ["architect", "ux_expert"] # Validate each other
validation_timeout: "3_minutes"
```
This Parallel Execution Engine dramatically improves system performance by executing independent agents simultaneously while maintaining data consistency and quality through intelligent coordination mechanisms.