%% SCRAP: experiments/campaigns/l8_validation/README %% SOURCE: docs/working/experiments/campaigns/l8_validation/README.md %% STATUS: CURRENT %% FITS: experiments/ch-l8-map %% EDITORIAL: lifted — prose rewritten to press voice \section{L8 Jacquard Mode Selector Validation Experiment} This experiment validates the L8 Jacquard mode selector by comparing dynamic adaptive mode switching against static optimal configurations across five workload types. Its empirical basis is the $2^7$ factorial DoE (38{,}400 runs), which identified L1 and L4 as harmful and established workload-specific optimal configurations for L2, L3, L5, and L6. %% PATENT: the L8 Jacquard dynamic mode selector is patent-adjacent. %% Do not draft claims here. \subsection{Experimental Design} \textbf{Type:} $8 \times 5$ factorial design. \textbf{Independent variables:} control strategy (8 levels) and workload type (5 levels). \textbf{Primary dependent variables:} \texttt{ns\_per\_word} and \texttt{cv}. \subsubsection{Control Strategies} \begin{center} \begin{tabular}{llrrrrrrrl} \toprule Strategy & L1 & L2 & L3 & L4 & L5 & L6 & L7 & Description \\ \midrule L8\_ADAPTIVE & 0 & rt & rt & 0 & rt & rt & 1 & Dynamic switching \\ C0\_BASELINE & 0 & 0 & 0 & 0 & 0 & 0 & 1 & Minimal \\ C4\_TEMPORAL & 0 & 0 & 1 & 0 & 0 & 0 & 1 & Decay only \\ C7\_FULL\_INF & 0 & 0 & 1 & 0 & 1 & 1 & 1 & Full inference \\ C9\_DIVERSE\_DECAY & 0 & 1 & 0 & 0 & 0 & 1 & 1 & Window + decay\_inf \\ C11\_DIVERSE\_INF & 0 & 1 & 0 & 0 & 1 & 1 & 1 & Window + inference \\ C12\_DIVERSE\_TEMP & 0 & 1 & 1 & 0 & 0 & 0 & 1 & Window + decay \\ ALL\_ON & 0 & 1 & 1 & 0 & 1 & 1 & 1 & All except L1/L4 \\ \bottomrule \end{tabular} \end{center} (rt = runtime-selected by L8 mode selector) \subsubsection{Workload Types} \begin{center} \begin{tabular}{lll} \toprule Workload & Characteristics & Expected L8 Mode \\ \midrule STABLE & Predictable, repetitive & C0 or C4 \\ DIVERSE & High entropy, mixed operations & C9, C11, or C12 \\ VOLATILE & High CV, random branching & C1 or C7 \\ TEMPORAL & Strong locality, nested loops & C4 or C12 \\ TRANSITION & Phase shifts between workloads & Adaptive \\ \bottomrule \end{tabular} \end{center} \subsection{Hypotheses} \begin{description} \item[H1 (Performance).] L8\_ADAPTIVE matches or exceeds the best static configuration per workload, within a 5\% margin. \item[H2 (Stability).] L8\_ADAPTIVE shows lower overall CV than any single static configuration across all workloads. \item[H3 (Adaptation).] The L8 mode distribution correlates with workload characteristics. \item[H4 (Generalization).] L8\_ADAPTIVE outperforms all static configurations on the TRANSITION workload. \end{description} \subsection{Running the Experiment} \begin{lstlisting}[language=bash] # 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 \end{lstlisting} \subsection{Analysis} \begin{lstlisting}[language=bash] Rscript analyze_l8.R l8_validation_YYYYMMDD_HHMMSS \end{lstlisting} Expected plots: ANOVA interaction plot (strategy $\times$ workload), L8 mode distribution per workload, Pareto frontier (speed vs.\ stability), and convergence curves showing mode switches. \subsection{Success Criteria} \begin{enumerate} \item L8\_ADAPTIVE is at most 5\% slower than the best static configuration per workload. \item L8\_ADAPTIVE exhibits the lowest CV across all workloads. \item L8 mode selections align with expected workload-specific patterns. \item L8\_ADAPTIVE dominates all static configurations on TRANSITION. \end{enumerate}