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