paper(§5): add roofline, capacity planning, parallelism selection subsections

Three new subsections at the top of §5, motivated by the deployment-sizing
questions the analytical visualization tool exposes:

- 5.1 Roofline Analysis — B*, L*, short vs long context batch effect
  (measured: 19× per-token cost reduction at short context, 28% at long)
- 5.2 Capacity Planning — 3-axis sizing (weights / KV / SLO), SLO targets,
  regime rules, deployment templates, per-axis playbook
- 5.3 Parallelism Selection — TP × CP × PP × DP × EP comparison,
  symptom-driven axis selection, add/stop criteria, misconceptions

Restructure:
- 05-gqa.tex trimmed to section header + intro
- Existing 5.4-5.7 content (placement, short/long ctx, composite) moved
  to 05x-fused-kernel.tex
- Summary extracted to 05z-summary.tex, cross-refs updated
- main.tex \input order sets the requested subsection sequence
- lmodern loaded to satisfy microtype font-expansion

Two new figures generated from tests/analytical_visualization/chip_roofline:
- roofline_short_context.png (S_kv=8K, batch wins)
- roofline_long_context.png (S_kv=1M, batch stalls at KV floor)
- Generator: tests/analytical_visualization/_gen_roofline_paper_figs.py

4 tables (regime rules, deployment templates, playbook, parallelism
criteria) use table* so they span both columns without overflow.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

docs/report/1H-codesign-paper/sections/05c-parallelism-selection.tex

@@ -0,0 +1,91 @@
+\subsection{Parallelism Selection: TP $\times$ CP $\times$ PP $\times$ DP $\times$ EP}
+\label{sec:parallelism-selection}
+
+Given a capacity-feasible layout (\S\ref{sec:capacity-planning}), the
+remaining decision is \emph{how to shard}: which axes to enable and at
+what degrees. Memory is the feasibility filter; once you fit, the
+design problem is minimising \emph{exposed} communication (communication
+that could not be overlapped with compute). The core principle is to
+\textbf{rank techniques by how much they communicate per unit of
+compute, and assign the chattiest ones to the fastest links.}
+
+\begin{table*}[h]
+\centering
+\small
+\caption{Parallelism axes at a glance. TP AllReduce volume does not
+shrink with degree — only compute does — which sets its practical
+ceiling near a fast-link (NVLink / intra-SIP) domain.}
+\label{tab:parallelism-compare}
+\begin{tabular}{@{}l l l l l@{}}
+\toprule
+Axis & Shards & Comm pattern & Frequency & Hard ceiling \\
+\midrule
+DP & optimizer state (w/ ZeRO) & AllReduce (grads) & 1$\times$/step & critical batch \\
+TP & weights + acts + KV heads & AllReduce & 2$\times$/layer & fast-link domain; $\lesssim h_{kv}$ \\
+PP & weights + KV by layer & P2P activation hand-off & per stage boundary & $n_{\text{layers}}$ \\
+CP & activations + KV by position & Ring P2P per hop & per layer (overlappable) & $\mathrm{seq\_len} / \mathrm{block}$ \\
+EP & expert weights (MoE only) & All-to-all & 2$\times$/MoE layer & $n_{\text{experts}}$ \\
+\bottomrule
+\end{tabular}
+\end{table*}
+
+\paragraph{Symptom-driven axis selection.} The dominant problem dictates
+the first knob to try (Table~\ref{tab:parallelism-problem}).
+
+\begin{table}[h]
+\centering
+\small
+\caption{Which axis to reach for first, by dominant problem.}
+\label{tab:parallelism-problem}
+\begin{tabular}{@{}l l@{}}
+\toprule
+Dominant problem & First axis \\
+\midrule
+Weight memory doesn't fit & TP within a fast domain \\
+KV of ONE long sequence & CP \\
+KV for MANY sequences & DP replicas \\
+Single-request TPOT & TP ($\lesssim 8$) \\
+Aggregate throughput & Outer DP \\
+Model spans multiple nodes & TP intra-node, PP inter-node \\
+MoE expert weight memory & EP \\
+\bottomrule
+\end{tabular}
+\end{table}
+
+\paragraph{When to add, when to stop.} Every axis has a natural
+saturation point past which further degree hurts more than it helps
+(Table~\ref{tab:parallelism-criteria}). Sizing decisions are almost
+always constrained by two axes simultaneously (e.g.\ TP by NVLink
+domain and $h_{kv}$; CP by ring-hop hiding and per-rank block size).
+
+\begin{table*}[t]
+\centering
+\small
+\caption{Add / stop criteria per axis.}
+\label{tab:parallelism-criteria}
+\begin{tabular}{@{}l l l@{}}
+\toprule
+Axis & Add when & Stop when \\
+\midrule
+DP & more independent requests & global batch $>$ critical \\
+TP & weights need sharding or TPOT tight & collectives dominate; local GEMMs shrink \\
+PP & depth too large; TP would cross slow links & bubble $>$ $\sim$10\% \\
+CP & one sequence needs position sharding & ring hops can't overlap compute \\
+EP & MoE expert memory & expert GEMMs too small; routing imbalance \\
+\bottomrule
+\end{tabular}
+\end{table*}
+
+\paragraph{Common misconceptions.} Three widely repeated rules survive
+contact with real workloads only partially:
+\emph{(i)} memory is not just a feasibility filter but a continuous
+performance variable --- more free HBM enables larger $B$, more prefix
+cache, higher throughput even after weights fit;
+\emph{(ii)} the ``TP $\leq h_{kv}$'' ceiling is an efficiency
+preference, not a correctness constraint --- vLLM and others support
+KV-head replication and head-dim splitting for TP $>$ $h_{kv}$;
+\emph{(iii)} ``always start at TP=8'' is disproven by public
+disclosures (DeepSeek-V3 inference uses TP=4, some MLPs at TP=1;
+DeepSeek-V3 training uses PP=16 + EP=64 with no TP), which shows the
+right starting point is the smallest TP that fits memory and meets
+latency, followed by measurement.