feat(experiments): per-second GPU util sampler in E4-pressured sweep

Background nvidia-smi poller runs at 1 Hz for all 4 GPUs throughout
the sweep, writing CSV to $OUTPUT/gpu_util.csv. Captures:
  timestamp_iso, gpu_index, util_pct, mem_used_MiB, mem_total_MiB,
  sm_clock_MHz, power_W, temperature_C

Sampler is started before benchmark-live and torn down via trap on
EXIT/INT/TERM so it always cleans up even if the run is killed.

This data lets us plot time-windowed wall-clock GPU utilization
(per-card) so we can answer "is concurrency the bottleneck or is
each D's per-session decode the bottleneck" — a question that
came up during E4-v3 / v5 analysis.

scripts/sweep_e4_pressured.sh

@@ -54,6 +54,29 @@ log "OUTPUT=$OUTPUT"
 label=e4p_kvc_v2_d_to_p_sync_run1
 log "=== [E4p] $label starting ==="
 
+# Background GPU utilization sampler — every 1 s, all 4 GPUs, CSV output.
+GPU_CSV="$OUTPUT/gpu_util.csv"
+log "GPU sampling → $GPU_CSV (1 Hz, gpus 0-3)"
+echo "timestamp_iso,gpu_index,util_pct,mem_used_MiB,mem_total_MiB,sm_clock_MHz,power_W,temperature_C" > "$GPU_CSV"
+(
+  while true; do
+    ts_iso=$(date -u +%Y-%m-%dT%H:%M:%S.%3NZ)
+    nvidia-smi --query-gpu=index,utilization.gpu,memory.used,memory.total,clocks.sm,power.draw,temperature.gpu \
+               --format=csv,noheader,nounits 2>/dev/null \
+      | sed -e "s/^/${ts_iso},/" -e 's/ //g' >> "$GPU_CSV" || true
+    sleep 1
+  done
+) &
+GPU_SAMPLER_PID=$!
+log "GPU sampler pid=$GPU_SAMPLER_PID"
+
+cleanup_gpu_sampler() {
+  kill -9 "$GPU_SAMPLER_PID" 2>/dev/null || true
+  wait "$GPU_SAMPLER_PID" 2>/dev/null || true
+  log "GPU sampler stopped (output: $GPU_CSV, $(wc -l < "$GPU_CSV") rows)"
+}
+trap cleanup_gpu_sampler EXIT INT TERM
+
 uv run --no-sync python -m agentic_pd_hybrid.cli benchmark-live \
   --trace "$TRACE" \
   --output-root "$OUTPUT" \