LithosAnanake/docs/working/experiments/campaigns/l8_validation

L8 Jacquard Mode Selector Validation Experiment

Overview

Validates the L8 Jacquard mode selector by comparing dynamic adaptive mode switching against static optimal configurations across diverse workload types.

Experimental Design

Type: 8×5 Factorial Design Independent Variables:

• Control Strategy (8 levels): L8_ADAPTIVE + 7 static configs
• Workload Type (5 levels): STABLE, DIVERSE, VOLATILE, TEMPORAL, TRANSITION

Dependent Variables:

• Primary: ns_per_word, cv (coefficient of variation)
• Secondary: Mode distribution (L8 only), mode switches, convergence time

Total Runs: 8 strategies × 5 workloads × N reps

Control Strategies

Strategy	L1	L2	L3	L4	L5	L6	L7	Description
L8_ADAPTIVE	0	runtime	runtime	0	runtime	runtime	1	Dynamic mode switching
C0_BASELINE	0	0	0	0	0	0	1	Minimal (baseline)
C4_TEMPORAL	0	0	1	0	0	0	1	Decay only (DoE rank #6)
C7_FULL_INF	0	0	1	0	1	1	1	Full inference (DoE ranks #2,#3)
C9_DIVERSE_DECAY	0	1	0	0	0	1	1	Window + decay_inf (DoE rank #5)
C11_DIVERSE_INF	0	1	0	0	1	1	1	Window + inference (DoE rank #4)
C12_DIVERSE_TEMPORAL	0	1	1	0	0	0	1	Window + decay (DoE rank #1)
ALL_ON	0	1	1	0	1	1	1	Everything except L1/L4

Workload Types

Workload	Characteristics	Expected L8 Mode
STABLE	Predictable, repetitive (Fibonacci, factorial)	C0 or C4
DIVERSE	High entropy (mixed ops, string ops, stack churn)	C9, C11, C12
VOLATILE	High CV (random branching, nested conditionals)	C1, C7
TEMPORAL	Strong locality (nested loops, hot words)	C4, C12
TRANSITION	Phase shifts (STABLE→DIVERSE→VOLATILE)	Adaptive

Hypotheses

H1 (Performance): L8_ADAPTIVE matches or exceeds best static config per workload (≤5% margin)

H2 (Stability): L8_ADAPTIVE shows lower overall CV than any single static config

H3 (Adaptation): L8 mode distribution correlates with workload characteristics

H4 (Generalization): L8_ADAPTIVE outperforms static configs on TRANSITION workload

Usage

# Quick test (10 reps = 400 runs, ~8 minutes)
cd experiments/l8_validation
./run_l8_validation.sh 10

# Standard validation (50 reps = 2,000 runs, ~40 minutes)
./run_l8_validation.sh 50

# High precision (100 reps = 4,000 runs, ~80 minutes)
./run_l8_validation.sh 100

Output

Results directory: l8_validation_YYYYMMDD_HHMMSS/

• l8_validation_results.csv - Raw experimental data
• conditions_raw.txt - Ordered conditions
• conditions_randomized.txt - Randomized run order
• init_original.4th.backup - Backup of original init file

Analysis

# Run R analysis (after experiment completes)
cd experiments/l8_validation
Rscript analyze_l8.R l8_validation_YYYYMMDD_HHMMSS

Expected plots:

• ANOVA interaction plot (strategy × workload)
• L8 mode distribution per workload
• Pareto frontier (speed vs stability)
• Convergence curves (L8 mode switches)

Data-Driven Design

This experiment is grounded in the 2^7 DoE results (300 reps, 38,400 runs):

• L1/L4 disabled: Harmful in 86%/100% of top 5% configs
• L7 enabled: Beneficial in 71% of top 5% configs
• L2/L3/L5/L6 contextual: Static optimal configs vary by workload
• L8 hypothesis: Dynamic switching should match workload-specific optimal configs

Success Criteria

1. L8 ≤ 5% slower than best static per workload
2. L8 shows lowest CV across all workloads
3. L8 modes align with expected patterns
4. L8 dominates on TRANSITION workload