docs(kvc): redesign gpu_utilization figure to lead with system-total compute
Reviewer feedback: the original gpu_utilization figure was confusing.
"P does prefill" is a trivial restatement of the architecture; the
figure didn't make clear what insight it was supposed to convey.
The non-trivial insight WAS in the figure but buried in per-GPU
breakdown details: KVC v2's total system compute is 3.47M tokens
vs DP's 5.17M -- a 33% reduction for the same 4449-request workload.
That's the result of session affinity actually converting to less
work, not just to better locality.
Redesigned the figure to lead with that finding:
Left panel (NEW): system-wide compute as two stacked bars
- KVC: P heavy prefill (1.07M) + D append-prefill (1.39M) + decode (1.01M)
- DP: full prefill (4.17M) + decode (1.00M)
- Big "-33% total compute" badge bracketed by an arrow between the
bar tops makes the headline number unmissable
Right panel (kept, simplified): per-GPU work distribution
- Same color coding as the left panel, so the architecture story
flows from "what work the system does" to "where it happens"
- In-panel annotation boxes describe the two architectural shapes
(specialized P + light D vs uniform fused workers)
- Removed the second legend that was overlapping bars
Doc §4.5 rewritten to match:
- Old title: "[辩驳 critic] Prefill GPU 90%+ 闲置 是设计意图，不是浪费"
(inside-baseball framing that confused external readers)
- New title: "KVC 的 compute 经济：session affinity 让系统总 compute 减少 33%"
(leads with the non-trivial finding)
- Body presents 3.47M vs 5.17M directly, decomposes into prefill /
decode segments, shows why session affinity converts to compute
reduction (mean uncached drops from 952 to 341 on the fast path)
- Cross-references §3.5 (TPOT) to explain why "unequal GPU load"
is a design feature, not a bug
- Drops the audit-rebuttal framing; the rebuttal of "P is idle"
is now implicit in the system-total comparison
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
kzlin
@@ -1,24 +1,25 @@
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#!/usr/bin/env python3
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"""Per-GPU utilization breakdown: KVC 1P3D v2 vs 4-way DP CA.
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"""System compute economy: KVC 1P3D v2 vs 4-way DP CA.
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Generates docs/figures/gpu_utilization.png — two-panel:
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left: per-GPU request count
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right: per-GPU compute work (uncached prefill tokens + decode tokens, stacked)
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Generates docs/figures/gpu_utilization.png -- two-panel:
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left: total system compute (stacked by work type)
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right: per-GPU compute distribution (specialized vs fused)
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The point of the figure is to push back on the naïve reading
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"KVC's prefill GPU is idle 90% of the time, so KVC is using fewer GPUs."
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The punchline is the TOTAL system compute reduction:
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KVC v2 system: 3.47 M tokens of compute (1.07 P-prefill + 1.39 D-append + 1.01 decode)
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DP 4-way: 5.17 M tokens of compute (4.17 full-prefill + 1.00 decode)
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→ KVC does 33% LESS compute for the SAME workload (same 4449 requests).
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By request count, the prefill GPU is indeed touched by only ~8% of requests.
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By compute work, the prefill GPU bears comparable per-GPU load to each
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decode GPU — it is a low-frequency, high-cost safety net for cache misses,
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not idle capacity.
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This is the non-trivial finding: session affinity converts to reduced
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system-wide work, not just locality. The per-GPU panel then explains
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the architectural shape: KVC concentrates heavy prefill on a specialized
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P worker, leaves D workers with light append + decode; DP forces every
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worker to absorb the full prefill load mixed with decode.
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Work attribution:
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KVC direct-to-D path: prefill happens locally on the assigned D worker
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(append-prefill of `uncached_tokens` tokens).
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KVC seed/reseed/fallback path: prefill happens on prefill-0
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(full uncached_tokens), decode on assigned D.
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DP: all work on assigned direct-N worker.
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The earlier version of this figure showed per-GPU request count + per-GPU
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compute and was confusing to external reviewers ("P doing prefill is
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trivial"). This version leads with the system-total comparison, which IS
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the non-trivial result.
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Aborted / errored requests are excluded.
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"""
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@@ -64,172 +65,211 @@ def main() -> None:
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dp = [r for r in load(DP) if not is_failed(r)]
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# ------------------------------------------------------------------
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# KVC per-GPU attribution
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# KVC per-GPU + per-work-type attribution
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# ------------------------------------------------------------------
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kvc_req_count = defaultdict(int)
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kvc_prefill_tokens = defaultdict(int) # uncached prefill compute
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kvc_prefill_tokens = defaultdict(int)
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kvc_decode_tokens = defaultdict(int)
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for r in kvc:
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d = r["assigned_decode_node"] # decode-0/1/2
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p = r["assigned_prefill_node"] # prefill-0
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d = r["assigned_decode_node"]
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p = r["assigned_prefill_node"]
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mode = r.get("execution_mode", "")
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if mode == "kvcache-direct-to-d-session":
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# P is bypassed entirely; D does the append-prefill + decode
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kvc_req_count[d] += 1
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# P bypassed; D does small append-prefill + decode
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kvc_prefill_tokens[d] += uncached(r)
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kvc_decode_tokens[d] += out_tokens(r)
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else:
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# P does the full prefill; D handles decode
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kvc_req_count[p] += 1
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kvc_req_count[d] += 1 # decode side still counts
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# P does heavy prefill; D handles decode
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kvc_prefill_tokens[p] += uncached(r)
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kvc_decode_tokens[d] += out_tokens(r)
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# ------------------------------------------------------------------
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# DP per-GPU attribution (fused P+D on every worker)
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# ------------------------------------------------------------------
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dp_req_count = defaultdict(int)
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dp_prefill_tokens = defaultdict(int)
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dp_decode_tokens = defaultdict(int)
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for r in dp:
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w = r["assigned_decode_node"] # direct-0..3
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dp_req_count[w] += 1
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w = r["assigned_decode_node"]
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dp_prefill_tokens[w] += uncached(r)
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dp_decode_tokens[w] += out_tokens(r)
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# ------------------------------------------------------------------
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# Build ordered GPU list, KVC then DP
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# Aggregate work by category for the left panel
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# ------------------------------------------------------------------
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kvc_p_prefill = kvc_prefill_tokens.get("prefill-0", 0)
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kvc_d_prefill = sum(v for k, v in kvc_prefill_tokens.items() if k.startswith("decode-"))
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kvc_d_decode = sum(kvc_decode_tokens.values())
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kvc_total = kvc_p_prefill + kvc_d_prefill + kvc_d_decode
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dp_prefill_total = sum(dp_prefill_tokens.values())
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dp_decode_total = sum(dp_decode_tokens.values())
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dp_total = dp_prefill_total + dp_decode_total
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M = 1e6
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saving_pct = (1 - kvc_total / dp_total) * 100
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# ------------------------------------------------------------------
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# Colors
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# ------------------------------------------------------------------
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KVC_P_COLOR = "#E89D44" # orange — P GPU
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KVC_D_PREF_COLOR = "#7AB6D9" # light blue — D-side small append-prefill
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KVC_D_DEC_COLOR = "#1F77B4" # dark blue — D-side decode
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DP_PREF_COLOR = "#E07474" # light red — DP full prefill
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DP_DEC_COLOR = "#D62728" # dark red — DP decode
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fig, axes = plt.subplots(1, 2, figsize=(15, 7.0))
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# ==================================================================
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# Left panel: System-wide compute, stacked by work type
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# ==================================================================
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ax = axes[0]
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x = np.array([0, 1])
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bar_w = 0.55
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# KVC stack: P-prefill (bottom orange) + D-prefill (light blue) + D-decode (dark blue)
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ax.bar(0, kvc_p_prefill / M, bar_w, color=KVC_P_COLOR,
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edgecolor="black", linewidth=0.6,
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label="KVC: P-side heavy prefill (reseed / seed)")
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ax.bar(0, kvc_d_prefill / M, bar_w, bottom=kvc_p_prefill / M,
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color=KVC_D_PREF_COLOR, edgecolor="black", linewidth=0.6,
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label="KVC: D-side append-prefill (direct-to-D, small)")
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ax.bar(0, kvc_d_decode / M, bar_w,
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bottom=(kvc_p_prefill + kvc_d_prefill) / M,
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color=KVC_D_DEC_COLOR, edgecolor="black", linewidth=0.6,
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label="Decode (both)")
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# DP stack: full prefill (light red) + decode (dark red)
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ax.bar(1, dp_prefill_total / M, bar_w,
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color=DP_PREF_COLOR, edgecolor="black", linewidth=0.6,
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label="DP: fused worker prefill (full uncached)")
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ax.bar(1, dp_decode_total / M, bar_w, bottom=dp_prefill_total / M,
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color=DP_DEC_COLOR, edgecolor="black", linewidth=0.6,
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label="_nolegend_")
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# Inline labels for stack segments
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def stack_label(xpos, ypos, text, color="white", fontsize=10):
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ax.text(xpos, ypos, text, ha="center", va="center",
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fontsize=fontsize, color=color, fontweight="bold")
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stack_label(0, kvc_p_prefill / M / 2,
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f"P heavy prefill\n{kvc_p_prefill/M:.2f}M")
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stack_label(0, (kvc_p_prefill + kvc_d_prefill / 2) / M,
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f"D append-prefill\n{kvc_d_prefill/M:.2f}M",
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color="black")
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stack_label(0, (kvc_p_prefill + kvc_d_prefill + kvc_d_decode / 2) / M,
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f"D decode\n{kvc_d_decode/M:.2f}M")
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stack_label(1, dp_prefill_total / M / 2,
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f"Full prefill\n(every worker)\n{dp_prefill_total/M:.2f}M",
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color="black")
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stack_label(1, (dp_prefill_total + dp_decode_total / 2) / M,
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f"Decode\n{dp_decode_total/M:.2f}M")
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# Totals on top
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ax.text(0, kvc_total / M + 0.15, f"{kvc_total/M:.2f}M tokens",
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ha="center", va="bottom", fontsize=12, fontweight="bold",
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color="#1F77B4")
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ax.text(1, dp_total / M + 0.15, f"{dp_total/M:.2f}M tokens",
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ha="center", va="bottom", fontsize=12, fontweight="bold",
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color="#D62728")
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# Big savings annotation — placed centrally inside the panel,
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# bracketed by a horizontal arrow connecting the bar tops.
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headroom_top = max(kvc_total, dp_total) / M * 1.42
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arrow_y = max(kvc_total, dp_total) / M * 1.08
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text_y = max(kvc_total, dp_total) / M * 1.22
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ax.annotate("", xy=(0.78, arrow_y), xytext=(0.22, arrow_y),
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arrowprops=dict(arrowstyle="<->", color="#2C8C2C", lw=1.8))
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ax.text(
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0.5, text_y, f"−{saving_pct:.0f}%\ntotal compute",
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ha="center", va="center",
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fontsize=13, fontweight="bold", color="#2C8C2C",
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bbox=dict(facecolor="#E8F5E8", edgecolor="#2C8C2C", alpha=0.95, pad=5),
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)
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ax.set_xticks(x)
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ax.set_xlim(-0.5, 1.5)
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ax.set_xticklabels(["KVC 1P3D v2", "DP 4-way CA"], fontsize=12, fontweight="bold")
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ax.set_ylabel("Total system compute (millions of token-equivalents)", fontsize=11)
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ax.set_ylim(0, headroom_top)
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ax.set_title("System-wide compute economy | same 4449-request workload",
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fontsize=12, pad=10)
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ax.grid(axis="y", linestyle=":", alpha=0.4)
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ax.set_axisbelow(True)
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ax.legend(loc="upper left", fontsize=8.5, framealpha=0.95)
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# ==================================================================
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# Right panel: per-GPU breakdown showing the architectural shape
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# ==================================================================
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ax = axes[1]
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kvc_gpus = ["prefill-0", "decode-0", "decode-1", "decode-2"]
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dp_gpus = ["direct-0", "direct-1", "direct-2", "direct-3"]
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all_gpus = kvc_gpus + dp_gpus
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def get(d, k):
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return d.get(k, 0)
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counts = [get(kvc_req_count, g) for g in kvc_gpus] + \
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[get(dp_req_count, g) for g in dp_gpus]
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prefill_tk = [get(kvc_prefill_tokens, g) for g in kvc_gpus] + \
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[get(dp_prefill_tokens, g) for g in dp_gpus]
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decode_tk = [get(kvc_decode_tokens, g) for g in kvc_gpus] + \
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[get(dp_decode_tokens, g) for g in dp_gpus]
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# Display labels: P/D role + worker id
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labels = [
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"KVC P\nprefill-0",
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"KVC D\ndecode-0",
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"KVC D\ndecode-1",
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"KVC D\ndecode-2",
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"DP P+D\ndirect-0",
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"DP P+D\ndirect-1",
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"DP P+D\ndirect-2",
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"DP P+D\ndirect-3",
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"KVC\nP-only", "KVC\nD-0", "KVC\nD-1", "KVC\nD-2",
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"DP\nP+D-0", "DP\nP+D-1", "DP\nP+D-2", "DP\nP+D-3",
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]
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kvc_mask = [True, True, True, True, False, False, False, False]
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KVC_P_COLOR = "#E89D44" # orange — P GPU stands out
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KVC_D_COLOR = "#1F77B4" # blue
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DP_COLOR = "#D62728" # red
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bar_colors = [KVC_P_COLOR, KVC_D_COLOR, KVC_D_COLOR, KVC_D_COLOR,
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DP_COLOR, DP_COLOR, DP_COLOR, DP_COLOR]
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fig, axes = plt.subplots(1, 2, figsize=(15, 7.0))
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x = np.arange(len(all_gpus))
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# -- Left: per-GPU request count ----------------------------------
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ax = axes[0]
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bars = ax.bar(x, counts, color=bar_colors, edgecolor="black", linewidth=0.6)
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for xi, c in zip(x, counts):
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ax.text(xi, c + max(counts) * 0.015, f"{c:,}",
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ha="center", va="bottom", fontsize=9.5)
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ax.set_xticks(x)
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ax.set_xticklabels(labels, fontsize=9.5)
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ax.set_ylabel("Number of requests touching this GPU", fontsize=11)
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# Headroom for the annotation: extend ylim 35% above tallest bar
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ax.set_ylim(0, max(counts) * 1.40)
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ax.set_title("Per-GPU request count\n(naïve view: P seems idle)",
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fontsize=12, pad=24)
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ax.grid(axis="y", linestyle=":", alpha=0.4)
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ax.set_axisbelow(True)
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prefill_M = ([kvc_prefill_tokens.get(g, 0) / M for g in kvc_gpus]
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+ [dp_prefill_tokens.get(g, 0) / M for g in dp_gpus])
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decode_M = ([kvc_decode_tokens.get(g, 0) / M for g in kvc_gpus]
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+ [dp_decode_tokens.get(g, 0) / M for g in dp_gpus])
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# Annotate: KVC P GPU is "low frequency"
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# Place in upper-right area (over DP group) so it doesn't sit on KVC D bars
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p_idx = 0
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ax.annotate(
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f"P GPU only sees\n"
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f"{counts[p_idx]:,} requests\n"
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f"({counts[p_idx]/len(kvc)*100:.1f}% of all KVC requests)",
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xy=(p_idx, counts[p_idx]),
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xytext=(2.4, max(counts) * 1.20),
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fontsize=10, color=KVC_P_COLOR, fontweight="bold", ha="center",
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bbox=dict(facecolor="white", edgecolor=KVC_P_COLOR, alpha=0.92, pad=4),
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arrowprops=dict(arrowstyle="->", color=KVC_P_COLOR, lw=1.0),
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)
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# Color by group: orange for KVC P, blue for KVC D, red for DP
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bar_colors_prefill = [KVC_P_COLOR, KVC_D_PREF_COLOR, KVC_D_PREF_COLOR, KVC_D_PREF_COLOR,
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DP_PREF_COLOR, DP_PREF_COLOR, DP_PREF_COLOR, DP_PREF_COLOR]
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bar_colors_decode = [KVC_D_DEC_COLOR, KVC_D_DEC_COLOR, KVC_D_DEC_COLOR, KVC_D_DEC_COLOR,
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DP_DEC_COLOR, DP_DEC_COLOR, DP_DEC_COLOR, DP_DEC_COLOR]
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ax.bar(x, prefill_M, color=bar_colors_prefill,
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edgecolor="black", linewidth=0.5, label="Prefill compute")
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ax.bar(x, decode_M, bottom=prefill_M, color=bar_colors_decode,
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edgecolor="black", linewidth=0.5, hatch="///",
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alpha=0.75, label="Decode compute")
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# -- Right: per-GPU compute work (stacked prefill + decode) -------
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ax = axes[1]
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prefill_M = [t / 1e6 for t in prefill_tk]
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decode_M = [t / 1e6 for t in decode_tk]
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total_M = [p + d for p, d in zip(prefill_M, decode_M)]
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bars_p = ax.bar(x, prefill_M, color=[c for c in bar_colors],
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edgecolor="black", linewidth=0.6, label="Uncached prefill tokens",
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alpha=0.95)
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bars_d = ax.bar(x, decode_M, bottom=prefill_M, color=[c for c in bar_colors],
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edgecolor="black", linewidth=0.6, hatch="///",
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label="Decode tokens", alpha=0.55)
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for xi, t in zip(x, total_M):
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ax.text(xi, t + max(total_M) * 0.015, f"{t:.2f}M",
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ha="center", va="bottom", fontsize=9.5)
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ax.set_xticks(x)
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ax.set_xticklabels(labels, fontsize=9.5)
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ax.set_ylabel("Compute tokens (millions)", fontsize=11)
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# Headroom for the annotation
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ax.set_ylim(0, max(total_M) * 1.45)
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ax.set_title("Per-GPU compute work\n(work view: P is comparable to each D)",
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fontsize=12, pad=24)
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ax.set_ylabel("Compute (millions of token-equivalents)", fontsize=11)
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ax.set_ylim(0, max(total_M) * 1.30)
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ax.set_title("Where the work lives | specialized P + light D vs uniform fused workers",
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fontsize=12, pad=10)
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ax.grid(axis="y", linestyle=":", alpha=0.4)
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ax.set_axisbelow(True)
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# Legend placed at upper-left where bars are tallest is fine after raising ylim
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ax.legend(loc="upper left", fontsize=10, framealpha=0.95)
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# Annotate: KVC P GPU does similar work to each D.
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# Place over DP region (right side) so it doesn't sit on KVC D bars.
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ax.annotate(
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f"P GPU does {total_M[p_idx]:.2f}M tokens of prefill\n"
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f"— comparable per-GPU load to each KVC D worker\n"
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f"(KVC D avg = {np.mean(total_M[1:4]):.2f}M)",
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xy=(p_idx, total_M[p_idx]),
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xytext=(5.5, max(total_M) * 1.30),
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fontsize=10, color=KVC_P_COLOR, fontweight="bold", ha="center",
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bbox=dict(facecolor="white", edgecolor=KVC_P_COLOR, alpha=0.92, pad=4),
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arrowprops=dict(arrowstyle="->", color=KVC_P_COLOR, lw=1.0),
|
||||
# Separator + headline takeaways under the GROUP labels (in axes
|
||||
# fraction coords so they don't shift if ylim changes).
|
||||
ax.axvline(3.5, color="gray", linestyle="--", linewidth=1.0, alpha=0.5)
|
||||
ax.text(
|
||||
0.22, 0.97,
|
||||
f"KVC: P specialized for heavy prefill\nD workers ~{np.mean(total_M[1:4]):.2f}M each (light)",
|
||||
transform=ax.transAxes, ha="center", va="top", fontsize=9.5,
|
||||
bbox=dict(facecolor="#FFFAE6", edgecolor="#888", alpha=0.92, pad=4),
|
||||
)
|
||||
ax.text(
|
||||
0.78, 0.97,
|
||||
f"DP: every worker {np.mean(total_M[4:]):.2f}M (fused)\nfull prefill interleaved with decode",
|
||||
transform=ax.transAxes, ha="center", va="top", fontsize=9.5,
|
||||
bbox=dict(facecolor="#FFE8E8", edgecolor="#888", alpha=0.92, pad=4),
|
||||
)
|
||||
|
||||
# Separator + group labels (placed in axes-fraction coords, below subplot
|
||||
# title at pad=24 we now have safe room for these at y_axes_frac ≈ 1.02)
|
||||
for ax in axes:
|
||||
ax.axvline(3.5, color="gray", linestyle="--", linewidth=1.0, alpha=0.5)
|
||||
ax.text(0.25, 1.02, "KVC 1P3D",
|
||||
transform=ax.transAxes, ha="center", va="bottom",
|
||||
fontsize=11.5, fontweight="bold", color="#444",
|
||||
bbox=dict(facecolor="#F2F2F2", edgecolor="#888",
|
||||
alpha=0.85, pad=3))
|
||||
ax.text(0.75, 1.02, "DP 4-way CA",
|
||||
transform=ax.transAxes, ha="center", va="bottom",
|
||||
fontsize=11.5, fontweight="bold", color="#444",
|
||||
bbox=dict(facecolor="#F2F2F2", edgecolor="#888",
|
||||
alpha=0.85, pad=3))
|
||||
# No second legend on the right panel — the colours are already
|
||||
# introduced in the left panel and the in-panel annotation boxes
|
||||
# explain what each group means. Decode being hatched is signalled
|
||||
# in the right-panel bar style itself.
|
||||
|
||||
fig.suptitle(
|
||||
"Per-GPU utilization: \"is KVC's prefill GPU wasted?\"\n"
|
||||
"Left view says yes (only 8% of requests); right view says no (comparable work to each D).",
|
||||
fontsize=13, y=1.02,
|
||||
"KVC v2 reduces system-wide compute by 33% vs DP 4-way CA, same workload (4449 requests).\n"
|
||||
"Mechanism: 91.6% of requests find their prefix cached on the affinity-pinned D worker\n"
|
||||
"(append-prefill = 341 tokens on avg), so the total prefill work the system must do is much smaller.",
|
||||
fontsize=12, y=1.05,
|
||||
)
|
||||
plt.tight_layout()
|
||||
plt.savefig(OUT, dpi=150, bbox_inches="tight")
|
||||
@@ -239,10 +279,19 @@ def main() -> None:
|
||||
# ------------------------------------------------------------------
|
||||
# Print numbers for doc reference
|
||||
# ------------------------------------------------------------------
|
||||
print("\n=== Per-GPU numbers ===")
|
||||
print(f"{'GPU':<22} {'requests':>10} {'prefill(M)':>12} {'decode(M)':>12} {'total(M)':>10}")
|
||||
for lbl, n, pM, dM in zip(labels, counts, prefill_M, decode_M):
|
||||
print(f" {lbl.replace(chr(10), ' '):<20} {n:>10} {pM:>12.3f} {dM:>12.3f} {pM+dM:>10.3f}")
|
||||
print("\n=== System totals ===")
|
||||
print(f"KVC v2 total: {kvc_total/M:.3f}M tokens")
|
||||
print(f" P heavy prefill: {kvc_p_prefill/M:.3f}M")
|
||||
print(f" D append-prefill: {kvc_d_prefill/M:.3f}M")
|
||||
print(f" D decode: {kvc_d_decode/M:.3f}M")
|
||||
print(f"DP 4w total: {dp_total/M:.3f}M tokens")
|
||||
print(f" Full prefill: {dp_prefill_total/M:.3f}M")
|
||||
print(f" Decode: {dp_decode_total/M:.3f}M")
|
||||
print(f"\nKVC vs DP: -{saving_pct:.1f}% total compute saved")
|
||||
|
||||
print("\n=== Per-GPU breakdown ===")
|
||||
for lbl, p, d in zip(labels, prefill_M, decode_M):
|
||||
print(f" {lbl.replace(chr(10), ' '):<14} prefill={p:.3f}M decode={d:.3f}M total={p+d:.3f}M")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
Reference in New Issue
Block a user