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EXO-AI 2025 Performance Baseline Metrics

Date: 2025-11-29 Version: 0.1.0 Benchmark Framework: Criterion 0.5

Executive Summary

This document establishes baseline performance metrics for the EXO-AI cognitive substrate. All measurements represent target performance on modern multi-core CPUs (e.g., AMD Ryzen 9 / Intel i9 class).

System Architecture Performance Profile

Cognitive Operations (Real-time Tier)

  • Latency Target: < 1ms for interactive operations
  • Throughput Target: 1000+ ops/sec per component

Batch Processing (High-throughput Tier)

  • Latency Target: < 10ms for batch operations
  • Throughput Target: 10,000+ items/sec

Distributed Coordination (Consensus Tier)

  • Latency Target: < 100ms for consensus rounds
  • Throughput Target: 100+ consensus/sec

Component Baselines

1. Manifold (Geometric Embedding)

Retrieval Performance

Concept Count Expected Latency Throughput Notes
100 20-30μs 35,000 queries/sec Small workspace
500 50-70μs 15,000 queries/sec Medium workspace
1,000 80-120μs 10,000 queries/sec Baseline target
5,000 300-500μs 2,500 queries/sec Large workspace

Optimization Threshold: > 150μs @ 1000 concepts

Deformation (Embedding) Performance

Batch Size Expected Latency Throughput Notes
10 100-200μs 60,000 embeds/sec Micro-batch
50 500-800μs 65,000 embeds/sec Baseline target
100 800-1,200μs 85,000 embeds/sec Standard batch
500 4-6ms 90,000 embeds/sec Large batch

Optimization Threshold: > 1.5ms @ 100 batch size

Specialized Operations

Operation Expected Latency Notes
Local Adaptation 30-50μs Per-concept learning
Curvature Computation 5-10μs Geometric calculation
Geodesic Distance 8-15μs Manifold distance

2. Hypergraph (Relational Reasoning)

Edge Creation Performance

Nodes per Edge Expected Latency Throughput Notes
2 (standard edge) 1-3μs 400,000 edges/sec Binary relation
5 3-6μs 180,000 edges/sec Baseline target
10 8-12μs 90,000 edges/sec Medium hyperedge
20 18-25μs 45,000 edges/sec Large hyperedge
50 50-80μs 15,000 edges/sec Very large hyperedge

Optimization Threshold: > 8μs @ 5 nodes

Query Performance

Total Edges Expected Latency Throughput Notes
100 10-20μs 60,000 queries/sec Small graph
500 30-50μs 25,000 queries/sec Medium graph
1,000 40-70μs 16,000 queries/sec Baseline target
5,000 100-200μs 7,000 queries/sec Large graph

Optimization Threshold: > 100μs @ 1000 edges

Complex Operations

Operation Expected Latency Notes
Pattern Matching 80-150μs 3-node patterns in 500-edge graph
Subgraph Extraction 150-300μs Depth-2, 10 seed nodes
Transitive Closure 500-1000μs 100-node graph

3. Temporal Coordinator (Causal Memory)

Causal Query Performance

Event Count Expected Latency Throughput Notes
100 20-40μs 30,000 queries/sec Small history
500 60-100μs 12,000 queries/sec Medium history
1,000 80-150μs 8,000 queries/sec Baseline target
5,000 300-600μs 2,200 queries/sec Large history

Optimization Threshold: > 200μs @ 1000 events

Memory Management

Operation Expected Latency Throughput Notes
Event Recording 2-5μs 250,000 events/sec Single event
Consolidation (500) 3-7ms - Periodic operation
Range Query 150-300μs 4,000 queries/sec 1-hour window
Causal Path (100) 400-700μs 1,700 paths/sec 100-hop path
Event Pruning (5000) 1-3ms - Maintenance operation

Optimization Threshold: > 5ms consolidation @ 500 events


4. Federation (Distributed Coordination)

CRDT Operations (Async)

Operation Count Expected Latency Throughput Notes
10 500-1000μs 12,000 ops/sec Small batch
50 2-4ms 14,000 ops/sec Medium batch
100 4-7ms 16,000 ops/sec Baseline target
500 20-35ms 16,000 ops/sec Large batch

Optimization Threshold: > 10ms @ 100 operations

Consensus Performance

Node Count Expected Latency Throughput Notes
3 20-40ms 35 rounds/sec Minimum quorum
5 40-70ms 17 rounds/sec Baseline target
7 60-100ms 12 rounds/sec Standard cluster
10 90-150ms 8 rounds/sec Large cluster

Optimization Threshold: > 100ms @ 5 nodes

Network Operations (Simulated)

Operation Expected Latency Notes
State Sync (100 items) 8-15ms Full state transfer
Cryptographic Sign 80-150μs Per message
Signature Verify 120-200μs Per signature
Gossip Round (10 nodes) 15-30ms Full propagation
Gossip Round (50 nodes) 80-150ms Large network

Scaling Characteristics

Expected Complexity Classes

Component Operation Complexity Notes
Manifold Retrieval O(n log n) With spatial indexing
Manifold Embedding O(d²) d = dimension (512)
Hypergraph Edge Creation O(k) k = nodes per edge
Hypergraph Query O(e) e = incident edges
Temporal Causal Query O(log n) With indexed DAG
Temporal Path Finding O(n + m) BFS/DFS on causal graph
Federation CRDT Merge O(n) n = operations
Federation Consensus O(n²) n = nodes (messaging)

Scalability Targets

Horizontal Scaling (via Federation):

  • Linear throughput scaling up to 10 nodes
  • Sub-linear latency growth (< 2x @ 10 nodes)

Vertical Scaling (single node):

  • Near-linear scaling with CPU cores (up to 8 cores)
  • Memory bandwidth becomes bottleneck > 16 cores

Performance Regression Detection

Critical Thresholds (Trigger Investigation)

  • 5% regression: Individual operation baselines
  • 10% regression: End-to-end workflows
  • 15% regression: Acceptable for major feature additions

Monitoring Strategy

  1. Pre-commit: Run quick benchmarks (< 30s)
  2. CI Pipeline: Full benchmark suite on main branch
  3. Weekly: Comprehensive baseline updates
  4. Release: Performance validation vs. previous release

Hardware Specifications (Reference)

Baseline Testing Environment:

  • CPU: 8-core modern processor (3.5+ GHz)
  • RAM: 32GB DDR4-3200
  • Storage: NVMe SSD
  • OS: Linux kernel 5.15+

Variance Expectations:

  • ±10% on different hardware generations
  • ±5% across benchmark runs
  • ±15% between architectures (AMD vs Intel)

Optimization Priorities

Priority 1: Critical Path (Target < 1ms)

  1. Manifold retrieval @ 1000 concepts
  2. Hypergraph queries @ 1000 edges
  3. Temporal causal queries @ 1000 events

Priority 2: Throughput (Target > 10k ops/sec)

  1. Manifold batch embedding
  2. Hypergraph edge creation
  3. CRDT merge operations

Priority 3: Distributed Latency (Target < 100ms)

  1. Consensus rounds @ 5 nodes
  2. State synchronization
  3. Gossip propagation

Benchmark Validation

Statistical Requirements

  • Iterations: 100+ per measurement
  • Confidence: 95% confidence intervals
  • Outliers: < 5% outlier rate
  • Warmup: 10+ warmup iterations

Reproducibility

  • Coefficient of variation < 10%
  • Multiple runs should differ by < 5%
  • Baseline comparisons use same hardware

Future Optimization Targets

Version 0.2.0 Goals

  • 20% improvement in manifold retrieval
  • 30% improvement in hypergraph queries
  • 15% improvement in consensus latency

Version 1.0.0 Goals

  • Sub-millisecond cognitive operations
  • 100k ops/sec throughput per component
  • 50ms consensus @ 10 nodes

Benchmark Maintainer: Performance Agent Review Cycle: Monthly Next Review: 2025-12-29