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║                     GPU TRAINING BENCHMARK - GAP ANALYSIS                         ║
║                          Agent 86 Report (2025-10-14)                             ║
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┌─────────────────────────────────────────────────────────────────────────────────┐
│                          BENCHMARK STATUS SUMMARY                                │
└─────────────────────────────────────────────────────────────────────────────────┘

┌───────────┬──────────────┬────────────────┬───────────────┬─────────────────────┐
│   Model   │   Status     │  Epoch Time    │  Peak VRAM    │   1K Epochs Est.    │
├───────────┼──────────────┼────────────────┼───────────────┼─────────────────────┤
│    DQN    │  ✅ TESTED   │   0.149 ms     │    135 MB     │    2.5 minutes      │
│    PPO    │  ✅ TESTED   │   181.9 ms     │    135 MB     │    3.0 minutes      │
│  MAMBA-2  │  ❌ MISSING  │   ??? ms       │   ~200-500 MB │    ??? minutes      │
│    TFT    │  ❌ MISSING  │   ??? ms       │  ~1500-2500MB │    ??? minutes      │
│   TLOB    │  ❌ EXCLUDED │   N/A          │     N/A       │     EXCLUDED        │
└───────────┴──────────────┴────────────────┴───────────────┴─────────────────────┘

Coverage: 50% (2/4 trainable models benchmarked)

┌─────────────────────────────────────────────────────────────────────────────────┐
│                        EXISTING BENCHMARK RESULTS                                │
│                        (Wave 152 - 2025-10-13)                                   │
└─────────────────────────────────────────────────────────────────────────────────┘

DQN (WorkingDQN):
  • Epochs tested: 500
  • Mean epoch time: 0.149 ms (149 microseconds)
  • 95% CI: [0.148, 0.150] ms
  • P50/P95/P99: 0.148 / 0.167 / 0.175 ms
  • Coefficient of variation: 6.5% (highly consistent)
  • Peak VRAM: 135 MB (3.3% of 4GB)
  • Batch size: 230
  • Stability: ⚠️  DIVERGING (loss 0.225 → 0.273)
  • Gradient health: ✅ Healthy (no NaN/Inf)
  • Training time (1K epochs): 2.5 minutes
  
PPO:
  • Epochs tested: 500
  • Mean epoch time: 181.9 ms
  • 95% CI: [181.3, 182.6] ms
  • P50/P95/P99: 181.4 / 194.7 / 202.9 ms
  • Coefficient of variation: 4.0% (highly consistent)
  • Peak VRAM: 135 MB (3.3% of 4GB)
  • Batch size: 230
  • Stability: ✅ CONVERGING (no warnings)
  • Gradient health: ✅ Healthy
  • Policy loss: 0.0665, Value loss: 0.3344
  • Training time (2K epochs): 6.1 minutes

┌─────────────────────────────────────────────────────────────────────────────────┐
│                         DECISION FRAMEWORK ANALYSIS                              │
└─────────────────────────────────────────────────────────────────────────────────┘

Current Decision (DQN + PPO only):
  Recommendation: ✅ local_gpu
  Total time: 0.101 hours (6.1 minutes)
  Local cost: $0.0023 (150W @ $0.15/kWh)
  Cloud cost: $0.053 (AWS g4dn.xlarge @ $0.526/hr)
  Rationale: "Total time 0.1h (<24h threshold)"

Projected Decision (All 4 models - EXTRAPOLATED):
  Model          Epochs    Est. Time
  ───────────────────────────────────
  DQN            1,000     2.5 min
  PPO            2,000     6.1 min
  MAMBA-2        1,000     ~20 min   (ESTIMATED from docs)
  TFT            1,500     ~12.5 min (ESTIMATED from docs)
  ───────────────────────────────────
  TOTAL                    ~41 min ✅ (<24h threshold)
  
  Recommendation: ✅ local_gpu (PRELIMINARY)
  Confidence: ⚠️  LOW (extrapolated, not measured)

┌─────────────────────────────────────────────────────────────────────────────────┐
│                              CRITICAL GAPS                                       │
└─────────────────────────────────────────────────────────────────────────────────┘

1. ❌ MAMBA-2 Benchmark Missing
   Impact: Cannot validate 4-6 week training timeline
   Risk: MAMBA-2 may be slower than estimated (SSM complexity)
   Module exists: ✅ ml/src/benchmark/mamba2_benchmark.rs (21KB)
   
2. ❌ TFT Benchmark Missing
   Impact: Cannot validate memory constraints (1.5-2.5GB on 4GB GPU)
   Risk: TFT may require batch_size=2, doubling training time
   Module exists: ✅ ml/src/benchmark/tft_benchmark.rs (23KB)
   
3. ⚠️  DQN Stability Issue
   Impact: Loss diverging, cannot deploy to production
   Risk: Requires hyperparameter tuning + retraining (1-2 days)
   Root cause: Unknown (learning rate / target update / replay buffer)

┌─────────────────────────────────────────────────────────────────────────────────┐
│                            WHY BENCHMARKS FAILED                                 │
└─────────────────────────────────────────────────────────────────────────────────┘

Root Cause: gpu_training_benchmark.rs coordinator only calls DQN/PPO benchmarks

Code Analysis (ml/examples/gpu_training_benchmark.rs:204-220):
  ✅ Step 3: Run DQN benchmark ← IMPLEMENTED
  ✅ Step 4: Run PPO benchmark ← IMPLEMENTED
  ❌ Step 5: Run MAMBA-2 benchmark ← MISSING
  ❌ Step 6: Run TFT benchmark ← MISSING

Required Changes:
  1. Add imports: Mamba2BenchmarkRunner, TftBenchmarkRunner
  2. Add methods: run_mamba2_benchmark(), run_tft_benchmark()
  3. Update BenchmarkReport struct (add mamba2_results, tft_results fields)
  4. Update compute_aggregate_metrics() (4 models instead of 2)
  5. Update print_summary() (display all 4 models)
  
Estimated effort: 100-150 lines of code (copy-paste from DQN/PPO)

┌─────────────────────────────────────────────────────────────────────────────────┐
│                              GPU HARDWARE STATUS                                 │
└─────────────────────────────────────────────────────────────────────────────────┘

Current State (2025-10-14 15:08:52):
  GPU: NVIDIA GeForce RTX 3050 Ti
  Driver: 580.65.06
  CUDA: 13.0
  VRAM: 3 MB / 4096 MB (0.07% used)
  Utilization: 0% (IDLE)
  Temperature: 59°C
  Power: 9W / 40W
  Persistence Mode: ON
  
Status: ✅ READY FOR IMMEDIATE BENCHMARKING

┌─────────────────────────────────────────────────────────────────────────────────┐
│                            IMMEDIATE NEXT STEPS                                  │
└─────────────────────────────────────────────────────────────────────────────────┘

Priority 1: Complete Benchmarks (2 hours total)
  □ Agent 87: Update gpu_training_benchmark.rs coordinator (15 min)
  □ Agent 87: Run full benchmark with MAMBA-2/TFT (30-60 min)
  □ Agent 87: Analyze results, update decision (30 min)
  
Priority 2: Fix DQN Stability (1-2 days)
  □ Agent 88: Debug diverging loss (hyperparameter tuning)
  □ Agent 88: Rerun DQN benchmark with fixes
  
Priority 3: Production Training (4-6 weeks)
  □ Agent 89: Download 90-day data (ES/NQ/ZN/6E)
  □ Agent 89: Data preprocessing + feature engineering
  □ Agent 89: Execute production training (timeline TBD)

┌─────────────────────────────────────────────────────────────────────────────────┐
│                                 CONCLUSION                                       │
└─────────────────────────────────────────────────────────────────────────────────┘

Benchmark Status: PARTIAL COMPLETE (50%)
  ✅ DQN/PPO benchmarked (Wave 152)
  ❌ MAMBA-2/TFT not benchmarked
  ❌ Cannot make informed 4-6 week training decision

GPU Readiness: ✅ IDLE AND READY (0% util, 59°C, 3MB VRAM)

Decision Confidence:
  DQN+PPO only: ✅ HIGH (empirical data, 6.1 min total)
  All 4 models: ⚠️  LOW (extrapolated, 41 min estimate)

Recommendation: Run full benchmark suite BEFORE committing to 4-6 week training.

Risk Assessment:
  HIGH: TFT memory bottleneck (1.5-2.5GB on 4GB GPU)
  MEDIUM: DQN divergence (requires fixing)
  LOW: GPU thermal throttling (24h+ training)

Timeline: 2 hours to complete benchmarks, 1-2 days to fix DQN, then ready for production.

═══════════════════════════════════════════════════════════════════════════════════
Report: AGENT_86_GPU_BENCHMARK_ANALYSIS.md (15KB)
Benchmark: AGENT_86_LATEST_BENCHMARK.json (26KB)
Generated: 2025-10-14 15:10:00 UTC
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