paper(gqa): table cleanup — drop measured-comm column, narrower fig, wrapped title

Removes the (measured) comm column, widens the Notes column with
shorter wrapped text, scales the table figure down, and wraps the
heading to two lines so it sits flush with the table.

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

scripts/paper/paper_plot_gqa_kv_sharding_diagram.py

@@ -163,40 +163,40 @@ def _draw_panel(ax, cfg):
 def _make_table_png() -> Path:
     """Slide-14 companion table: per-PE memory + comm for all 6 cases."""
     headers = ["Case", "Sharding", "KV / PE", "Fit",
-               "Comm/tok\n(analytical)", "Comm/tok\n(measured)", "Notes"]
+               "Comm/tok\n(analytical)", "Notes"]
     rows = [
         ("Case 1",   "Cube-Repl  ·  PE-repl",      "40 GB",  "✗",
-         "1.2 MB",  "1.25 MB",
+         "1.2 MB",
-         "no sharding — full KV on every PE"),
+         "no sharding —\nfull KV on every PE"),
         ("Case 2",   "Cube-SP    ·  PE-repl",      "5 GB",   "✗",
-         "3.8 MB",  "1.27 MB",
+         "3.8 MB",
-         "cube-axis sharded only"),
+         "cube-axis\nsharded only"),
         ("Case 3",   "Cube-Repl  ·  PE-SP",        "5 GB",   "✗",
-         "3.8 MB",  "1.39 MB",
+         "3.8 MB",
-         "PE-axis sharded only"),
+         "PE-axis\nsharded only"),
         ("Case 4",   "Cube-SP    ·  PE-TP-d_head", "640 MB", "✓",
-         "166 MB",  "162 MB",
+         "166 MB",
-         "d_head split intra-cube — partial-score AR ∝ S_kv"),
+         "d_head split intra-cube\npartial-score AR ∝ S_kv"),
         ("Case 5",   "Cube-TP-d_head  ·  PE-SP",   "640 MB", "✓",
-         "166 MB",  "162 MB",
+         "166 MB",
-         "d_head split inter-cube — partial-score AR on UCIe"),
+         "d_head split inter-cube\npartial-score AR on UCIe"),
         ("Case 6 ★", "Cube-SP    ·  PE-SP",        "640 MB", "✓",
-         "6.2 MB",  "1.41 MB",
+         "6.2 MB",
-         "S_kv split on both axes — (m,ℓ,O) AR only, S_kv-indep."),
+         "S_kv split both axes\n(m,ℓ,O) AR only"),
     ]
     accents = [_ACC["red"], _ACC["orange"], _ACC["orange"],
                _ACC["blue"], _ACC["blue"], _ACC["green"]]
 
-    fig, ax = plt.subplots(figsize=(20.0, 4.6))
+    fig, ax = plt.subplots(figsize=(15.0, 5.0))
     ax.set_axis_off()
 
     cell_data = [headers] + [list(r) for r in rows]
     tbl = ax.table(cellText=cell_data,
-                   colWidths=[0.07, 0.18, 0.08, 0.05, 0.12, 0.12, 0.38],
+                   colWidths=[0.07, 0.20, 0.09, 0.05, 0.14, 0.28],
                    cellLoc="center", loc="center")
     tbl.auto_set_font_size(False)
-    tbl.set_fontsize(11)
+    tbl.set_fontsize(10.5)
-    tbl.scale(1.0, 2.2)
+    tbl.scale(1.0, 2.4)
 
     n_cols = len(headers)
     n_rows = len(rows) + 1   # +1 header
@@ -237,9 +237,10 @@ def _make_table_png() -> Path:
     tbl[(0, n_cols - 1)].get_text().set_ha("left")
 
     fig.suptitle(
-        "GQA decode KV-sharding — per-PE memory & communication  "
+        "GQA decode KV-sharding — per-PE memory & communication\n"
-        "(LLaMA 70B GQA single KV-head group · S_kv = 1 M, FP16, 80 layers)",
+        "(LLaMA 70B GQA single KV-head group  ·  S_kv = 1 M, FP16, "
-        fontsize=12, y=0.97,
+        "80 layers)",
+        fontsize=11.5, y=0.94,
     )
     out = _OUT_DIR / "gqa_long_ctx_6cases_kv_sharding_table.png"
     fig.savefig(out, dpi=150, bbox_inches="tight")