Harden IPMI power probe timeout

- Split steady window into 6 equal slots: fp8/fp16/fp32/fp64/fp4 + combined
- Each precision phase runs bee-gpu-burn with --precision filter so PowerCVPct reflects single-kernel stability (not round-robin artifact)
- Add fp4 support in bee-gpu-stress.c for Blackwell (cc>=100) via existing CUDA_R_4F_E2M1 guard
- Weighted TOPS: fp64×2.0, fp32×1.0, fp16×0.5, fp8×0.25, fp4×0.125
- SyntheticScore = sum of weighted TOPS from per-precision phases
- MixedScore = sum from combined phase; MixedEfficiency = Mixed/Synthetic
- ComputeScore = SyntheticScore × (1 + MixedEfficiency × 0.3)
- ECC volatile counters sampled before/after each phase and overall
- DegradationReasons: ecc_uncorrected_errors, ecc_corrected_errors
- Report: per-precision stability table with ECC columns, methodology section
- Ramp-up history table redesign: GPU indices as columns, runs as rows

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

.gitignore

@@ -2,3 +2,4 @@
 .DS_Store
 dist/
 iso/out/
+build-cache/

audit/internal/platform/benchmark.go

@@ -73,6 +73,11 @@ var (
 	benchmarkIterationsPattern = regexp.MustCompile(`^([a-z0-9_]+)_iterations=(\d+)$`)
 )
 
+// benchmarkPrecisionPhases lists the precision categories run as individual
+// steady-state windows before the combined steady pass.  Order is from lowest
+// to highest power draw so thermal ramp-up is gradual.
+var benchmarkPrecisionPhases = []string{"fp8", "fp16", "fp32", "fp64", "fp4"}
+
 func (s *System) RunNvidiaBenchmark(ctx context.Context, baseDir string, opts NvidiaBenchmarkOptions, logFunc func(string)) (string, error) {
 	if ctx == nil {
 		ctx = context.Background()
@@ -120,6 +125,8 @@ func (s *System) RunNvidiaBenchmark(ctx context.Context, baseDir string, opts Nv
 	}
 
 	logFunc(fmt.Sprintf("NVIDIA benchmark profile=%s gpus=%s", spec.Name, joinIndexList(selected)))
+	var metricRows []GPUMetricRow
+	gpuBurnLog := filepath.Join(runDir, "gpu-burn.log")
 
 	// Server power characterization state — populated during per-GPU phases.
 	var serverIdleW, serverLoadedWSum float64
@@ -166,7 +173,7 @@ func (s *System) RunNvidiaBenchmark(ctx context.Context, baseDir string, opts Nv
 	cpuSamplesCh := startCPULoadSampler(cpuStopCh, 10)
 
 	if opts.ParallelGPUs {
-		runNvidiaBenchmarkParallel(ctx, verboseLog, runDir, selected, infoByIndex, opts, spec, logFunc, &result, calibPowerByIndex, &serverIdleW, &serverLoadedWSum, &serverIdleOK, &serverLoadedOK, &serverLoadedSamples)
+		runNvidiaBenchmarkParallel(ctx, verboseLog, runDir, selected, infoByIndex, opts, spec, logFunc, &result, calibPowerByIndex, &serverIdleW, &serverLoadedWSum, &serverIdleOK, &serverLoadedOK, &serverLoadedSamples, &metricRows, gpuBurnLog)
 	} else {
 
 		for _, idx := range selected {
@@ -199,7 +206,7 @@ func (s *System) RunNvidiaBenchmark(ctx context.Context, baseDir string, opts Nv
 				gpuResult.Notes = append(gpuResult.Notes, "baseline sampling failed: "+err.Error())
 			}
 			gpuResult.Baseline = summarizeBenchmarkTelemetry(baselineRows)
-		writeBenchmarkMetricsFiles(runDir, fmt.Sprintf("gpu-%d-baseline", idx), baselineRows)
+			appendBenchmarkMetrics(&metricRows, baselineRows, fmt.Sprintf("gpu-%d-baseline", idx))
 
 			// Sample server idle power once (first GPU only — server state is global).
 			if !serverIdleOK {
@@ -217,22 +224,67 @@ func (s *System) RunNvidiaBenchmark(ctx context.Context, baseDir string, opts Nv
 				"--devices", strconv.Itoa(idx),
 			}
 			logFunc(fmt.Sprintf("GPU %d: warmup (%ds)", idx, spec.WarmupSec))
-		warmupOut, _, warmupErr := runBenchmarkCommandWithMetrics(ctx, verboseLog, fmt.Sprintf("gpu-%d-warmup.log", idx), warmupCmd, nil, []int{idx}, runDir, fmt.Sprintf("gpu-%d-warmup", idx), logFunc)
-		_ = os.WriteFile(filepath.Join(runDir, fmt.Sprintf("gpu-%d-warmup.log", idx)), warmupOut, 0644)
+			warmupOut, warmupRows, warmupErr := runBenchmarkCommandWithMetrics(ctx, verboseLog, fmt.Sprintf("gpu-%d-warmup.log", idx), warmupCmd, nil, []int{idx}, logFunc)
+			appendBenchmarkMetrics(&metricRows, warmupRows, fmt.Sprintf("gpu-%d-warmup", idx))
+			appendBenchmarkStageLog(gpuBurnLog, "bee-gpu-burn", fmt.Sprintf("gpu-%d-warmup", idx), warmupOut)
 			if warmupErr != nil {
 				gpuResult.Notes = append(gpuResult.Notes, "warmup failed: "+warmupErr.Error())
 				result.GPUs = append(result.GPUs, finalizeBenchmarkGPUResult(gpuResult))
 				continue
 			}
 
+			// ── Per-precision stability phases ────────────────────────────────────────
+			// Run each precision category alone so PowerCVPct reflects genuine GPU
+			// power stability, not kernel-mix variance.
+			// Time budget: each phase gets steadySec/numPhases, minimum 60 s.
+			// SteadySec is split equally across all precision phases + 1 combined slot.
+			// Skipped phases (unsupported precision) are simply omitted; combined is fixed.
+			totalSlots := len(benchmarkPrecisionPhases) + 1
+			perPhaseSec := spec.SteadySec / totalSlots
+			if perPhaseSec < 60 {
+				perPhaseSec = 60
+			}
+			eccBase, _ := queryECCCounters(idx)
+			for _, prec := range benchmarkPrecisionPhases {
+				phaseCmd := []string{
+					"bee-gpu-burn",
+					"--seconds", strconv.Itoa(perPhaseSec),
+					"--size-mb", strconv.Itoa(opts.SizeMB),
+					"--devices", strconv.Itoa(idx),
+					"--precision", prec,
+				}
+				logFunc(fmt.Sprintf("GPU %d: %s stability phase (%ds)", idx, prec, perPhaseSec))
+				phaseLogName := fmt.Sprintf("gpu-%d-steady-%s", idx, prec)
+				eccBefore, _ := queryECCCounters(idx)
+				phaseOut, phaseRows, phaseErr := runBenchmarkCommandWithMetrics(ctx, verboseLog, phaseLogName+".log", phaseCmd, nil, []int{idx}, logFunc)
+				appendBenchmarkMetrics(&metricRows, phaseRows, phaseLogName)
+				appendBenchmarkStageLog(gpuBurnLog, "bee-gpu-burn", phaseLogName, phaseOut)
+				eccAfter, _ := queryECCCounters(idx)
+				if phaseErr != nil || len(phaseRows) == 0 {
+					continue
+				}
+				phase := BenchmarkPrecisionSteadyPhase{
+					Precision: prec,
+					Steady:    summarizeBenchmarkTelemetry(phaseRows),
+					ECC:       diffECCCounters(eccBefore, eccAfter),
+				}
+				for _, p := range parseBenchmarkBurnLog(string(phaseOut)).Profiles {
+					if p.Supported {
+						phase.TeraOpsPerSec += p.TeraOpsPerSec
+						phase.WeightedTeraOpsPerSec += p.WeightedTeraOpsPerSec
+					}
+				}
+				gpuResult.PrecisionSteady = append(gpuResult.PrecisionSteady, phase)
+			}
+
 			beforeThrottle, _ := queryThrottleCounters(idx)
 			steadyCmd := []string{
 				"bee-gpu-burn",
-			"--seconds", strconv.Itoa(spec.SteadySec),
+				"--seconds", strconv.Itoa(perPhaseSec),
 				"--size-mb", strconv.Itoa(opts.SizeMB),
 				"--devices", strconv.Itoa(idx),
 			}
-		logFunc(fmt.Sprintf("GPU %d: steady compute (%ds)", idx, spec.SteadySec))
+			logFunc(fmt.Sprintf("GPU %d: steady compute (combined, %ds)", idx, perPhaseSec))
 
 			// Sample server power via IPMI in parallel with the steady phase.
 			// We collect readings every 5s and average them.
@@ -268,7 +320,9 @@ func (s *System) RunNvidiaBenchmark(ctx context.Context, baseDir string, opts Nv
 				}
 			}()
 
-		steadyOut, steadyRows, steadyErr := runBenchmarkCommandWithMetrics(ctx, verboseLog, fmt.Sprintf("gpu-%d-steady.log", idx), steadyCmd, nil, []int{idx}, runDir, fmt.Sprintf("gpu-%d-steady", idx), logFunc)
+			steadyOut, steadyRows, steadyErr := runBenchmarkCommandWithMetrics(ctx, verboseLog, fmt.Sprintf("gpu-%d-steady.log", idx), steadyCmd, nil, []int{idx}, logFunc)
+			appendBenchmarkMetrics(&metricRows, steadyRows, fmt.Sprintf("gpu-%d-steady", idx))
+			appendBenchmarkStageLog(gpuBurnLog, "bee-gpu-burn", fmt.Sprintf("gpu-%d-steady", idx), steadyOut)
 			close(ipmiStopCh)
 			if loadedW, ok := <-ipmiResultCh; ok {
 				serverLoadedWSum += loadedW
@@ -276,8 +330,6 @@ func (s *System) RunNvidiaBenchmark(ctx context.Context, baseDir string, opts Nv
 				serverLoadedOK = true
 				logFunc(fmt.Sprintf("GPU %d: server loaded power (IPMI): %.0f W", idx, loadedW))
 			}
-
-		_ = os.WriteFile(filepath.Join(runDir, fmt.Sprintf("gpu-%d-steady.log", idx)), steadyOut, 0644)
 			afterThrottle, _ := queryThrottleCounters(idx)
 			if steadyErr != nil {
 				gpuResult.Notes = append(gpuResult.Notes, "steady compute failed: "+steadyErr.Error())
@@ -293,13 +345,16 @@ func (s *System) RunNvidiaBenchmark(ctx context.Context, baseDir string, opts Nv
 
 			gpuResult.Steady = summarizeBenchmarkTelemetry(steadyRows)
 			gpuResult.Throttle = diffThrottleCounters(beforeThrottle, afterThrottle)
+			if eccFinal, err := queryECCCounters(idx); err == nil {
+				gpuResult.ECC = diffECCCounters(eccBase, eccFinal)
+			}
 
 			cooldownRows, err := collectBenchmarkSamples(ctx, spec.CooldownSec, []int{idx})
 			if err != nil && err != context.Canceled {
 				gpuResult.Notes = append(gpuResult.Notes, "cooldown sampling failed: "+err.Error())
 			}
 			gpuResult.Cooldown = summarizeBenchmarkTelemetry(cooldownRows)
-		writeBenchmarkMetricsFiles(runDir, fmt.Sprintf("gpu-%d-cooldown", idx), cooldownRows)
+			appendBenchmarkMetrics(&metricRows, cooldownRows, fmt.Sprintf("gpu-%d-cooldown", idx))
 
 			gpuResult.Scores = scoreBenchmarkGPUResult(gpuResult)
 			gpuResult.DegradationReasons = detectBenchmarkDegradationReasons(gpuResult, result.Normalization.Status)
@@ -363,6 +418,7 @@ func (s *System) RunNvidiaBenchmark(ctx context.Context, baseDir string, opts Nv
 
 	result.Findings = buildBenchmarkFindings(result)
 	result.OverallStatus = benchmarkOverallStatus(result)
+	writeBenchmarkMetricsFiles(runDir, metricRows)
 
 	resultJSON, err := json.MarshalIndent(result, "", "  ")
 	if err != nil {
@@ -372,7 +428,7 @@ func (s *System) RunNvidiaBenchmark(ctx context.Context, baseDir string, opts Nv
 		return "", fmt.Errorf("write result.json: %w", err)
 	}
 
-	report := renderBenchmarkReportWithCharts(result, loadBenchmarkReportCharts(runDir, selected))
+	report := renderBenchmarkReportWithCharts(result)
 	if err := os.WriteFile(filepath.Join(runDir, "report.md"), []byte(report), 0644); err != nil {
 		return "", fmt.Errorf("write report.md: %w", err)
 	}
@@ -601,7 +657,6 @@ func queryBenchmarkGPUInfo(gpuIndices []int) (map[int]benchmarkGPUInfo, error) {
 	return nil, lastErr
 }
 
-
 func applyBenchmarkNormalization(ctx context.Context, verboseLog string, gpuIndices []int, infoByIndex map[int]benchmarkGPUInfo, result *NvidiaBenchmarkResult) []benchmarkRestoreAction {
 	if os.Geteuid() != 0 {
 		result.Normalization.Status = "partial"
@@ -704,7 +759,7 @@ func collectBenchmarkSamples(ctx context.Context, durationSec int, gpuIndices []
 	return rows, nil
 }
 
-func runBenchmarkCommandWithMetrics(ctx context.Context, verboseLog, name string, cmd []string, env []string, gpuIndices []int, runDir, baseName string, logFunc func(string)) ([]byte, []GPUMetricRow, error) {
+func runBenchmarkCommandWithMetrics(ctx context.Context, verboseLog, name string, cmd []string, env []string, gpuIndices []int, logFunc func(string)) ([]byte, []GPUMetricRow, error) {
 	stopCh := make(chan struct{})
 	doneCh := make(chan struct{})
 	var metricRows []GPUMetricRow
@@ -736,18 +791,65 @@ func runBenchmarkCommandWithMetrics(ctx context.Context, verboseLog, name string
 	close(stopCh)
 	<-doneCh
 
-	writeBenchmarkMetricsFiles(runDir, baseName, metricRows)
 	return out, metricRows, err
 }
 
-func writeBenchmarkMetricsFiles(runDir, baseName string, rows []GPUMetricRow) {
+func annotateBenchmarkMetricRows(rows []GPUMetricRow, stage string, offset float64) []GPUMetricRow {
+	if len(rows) == 0 {
+		return nil
+	}
+	out := make([]GPUMetricRow, len(rows))
+	for i, row := range rows {
+		row.Stage = stage
+		row.ElapsedSec += offset
+		out[i] = row
+	}
+	return out
+}
+
+func benchmarkMetricOffset(rows []GPUMetricRow) float64 {
+	if len(rows) == 0 {
+		return 0
+	}
+	var maxElapsed float64
+	for _, row := range rows {
+		if row.ElapsedSec > maxElapsed {
+			maxElapsed = row.ElapsedSec
+		}
+	}
+	return maxElapsed
+}
+
+func appendBenchmarkMetrics(allRows *[]GPUMetricRow, rows []GPUMetricRow, stage string) {
+	annotated := annotateBenchmarkMetricRows(rows, stage, benchmarkMetricOffset(*allRows))
+	*allRows = append(*allRows, annotated...)
+}
+
+func writeBenchmarkMetricsFiles(runDir string, rows []GPUMetricRow) {
 	if len(rows) == 0 {
 		return
 	}
-	_ = WriteGPUMetricsCSV(filepath.Join(runDir, baseName+"-metrics.csv"), rows)
-	_ = WriteGPUMetricsHTML(filepath.Join(runDir, baseName+"-metrics.html"), rows)
-	chart := RenderGPUTerminalChart(rows)
-	_ = os.WriteFile(filepath.Join(runDir, baseName+"-metrics-term.txt"), []byte(chart), 0644)
+	_ = WriteGPUMetricsCSV(filepath.Join(runDir, "gpu-metrics.csv"), rows)
+	_ = WriteGPUMetricsHTML(filepath.Join(runDir, "gpu-metrics.html"), rows)
+}
+
+func appendBenchmarkStageLog(path, source, stage string, raw []byte) {
+	if path == "" || len(raw) == 0 {
+		return
+	}
+	f, err := os.OpenFile(path, os.O_CREATE|os.O_APPEND|os.O_WRONLY, 0644)
+	if err != nil {
+		return
+	}
+	defer f.Close()
+	header := fmt.Sprintf("\n========== %s | stage=%s ==========\n", source, stage)
+	_, _ = f.WriteString(header)
+	if len(raw) > 0 {
+		_, _ = f.Write(raw)
+		if raw[len(raw)-1] != '\n' {
+			_, _ = f.WriteString("\n")
+		}
+	}
 }
 
 func parseBenchmarkBurnLog(raw string) benchmarkBurnParseResult {
@@ -811,8 +913,11 @@ func parseBenchmarkBurnLog(raw string) benchmarkBurnParseResult {
 			Iterations: profile.iterations,
 			Notes:      profile.notes,
 		}
+		w := precisionWeight(profile.category)
+		precision.Weight = w
 		if profile.supported && result.DurationSec > 0 && profile.m > 0 && profile.n > 0 && profile.k > 0 && profile.iterations > 0 {
 			precision.TeraOpsPerSec = (2.0 * float64(profile.m) * float64(profile.n) * float64(profile.k) * float64(profile.iterations)) / float64(result.DurationSec) / 1e12
+			precision.WeightedTeraOpsPerSec = precision.TeraOpsPerSec * w
 		}
 		result.Profiles = append(result.Profiles, precision)
 	}
@@ -841,6 +946,35 @@ func ensureBenchmarkProfile(profiles map[string]*benchmarkBurnProfile, name stri
 	return profile
 }
 
+// precisionWeight returns the fp32-equivalence factor for a precision category.
+// Each factor represents how much "real" numeric work one operation of that
+// type performs relative to fp32 (single precision = 1.0 baseline):
+//
+//	fp64  = 2.0  — double precision, 2× more bits per operand
+//	fp32  = 1.0  — single precision baseline
+//	fp16  = 0.5  — half precision
+//	fp8   = 0.25 — quarter precision
+//	fp4   = 0.125 — eighth precision
+//
+// Multiplying raw TOPS by the weight gives fp32-equivalent TOPS, enabling
+// cross-precision comparison on the same numeric scale.
+func precisionWeight(category string) float64 {
+	switch category {
+	case "fp64":
+		return 2.0
+	case "fp32_tf32":
+		return 1.0
+	case "fp16_bf16":
+		return 0.5
+	case "fp8":
+		return 0.25
+	case "fp4":
+		return 0.125
+	default:
+		return 1.0
+	}
+}
+
 func stripBenchmarkPrefix(line string) string {
 	if strings.HasPrefix(line, "[gpu ") {
 		if idx := strings.Index(line, "] "); idx >= 0 {
@@ -890,10 +1024,38 @@ func summarizeBenchmarkTelemetry(rows []GPUMetricRow) BenchmarkTelemetrySummary
 
 func scoreBenchmarkGPUResult(gpu BenchmarkGPUResult) BenchmarkScorecard {
 	score := BenchmarkScorecard{}
-	for _, precision := range gpu.PrecisionResults {
-		if precision.Supported {
-			score.ComputeScore += precision.TeraOpsPerSec
+
+	// SyntheticScore: sum of fp32-equivalent TOPS from per-precision phases.
+	// Each precision ran alone with full GPU dedicated — peak capability.
+	for _, p := range gpu.PrecisionSteady {
+		score.SyntheticScore += p.WeightedTeraOpsPerSec
 	}
+
+	// MixedScore: sum of fp32-equivalent TOPS from the combined phase.
+	// All precisions compete simultaneously — closer to real inference workloads.
+	for _, p := range gpu.PrecisionResults {
+		if p.Supported {
+			score.MixedScore += p.WeightedTeraOpsPerSec
+		}
+	}
+
+	// MixedEfficiency = MixedScore / SyntheticScore.
+	// Measures how well the GPU sustains throughput under concurrent mixed load.
+	// A healthy GPU scores ~0.8–0.95; severe degradation suggests bandwidth
+	// contention or scheduler inefficiency.
+	if score.SyntheticScore > 0 && score.MixedScore > 0 {
+		score.MixedEfficiency = score.MixedScore / score.SyntheticScore
+	}
+
+	// ComputeScore = SyntheticScore × (1 + MixedEfficiency × 0.3).
+	// SyntheticScore is the primary signal; MixedEfficiency adds up to +30%
+	// bonus for GPUs that handle mixed-precision concurrency well.
+	// Falls back to MixedScore alone when per-precision data is absent.
+	switch {
+	case score.SyntheticScore > 0:
+		score.ComputeScore = score.SyntheticScore * (1 + score.MixedEfficiency*0.3)
+	case score.MixedScore > 0:
+		score.ComputeScore = score.MixedScore
 	}
 	// PowerSustainScore: measures how close the GPU came to its rated TDP under
 	// a full-spectrum load (dcgmi targeted_power). 100 = exactly at rated TDP.
@@ -915,7 +1077,19 @@ func scoreBenchmarkGPUResult(gpu BenchmarkGPUResult) BenchmarkScorecard {
 	runtimeUS := math.Max(1, gpu.Steady.DurationSec*1e6)
 	thermalRatio := float64(gpu.Throttle.HWThermalSlowdownUS+gpu.Throttle.SWThermalSlowdownUS) / runtimeUS
 	score.ThermalSustainScore = clampScore(100 - thermalRatio*100)
-	score.StabilityScore = clampScore(100 - (gpu.Steady.ClockCVPct*4 + gpu.Steady.PowerCVPct*2 + gpu.Steady.ClockDriftPct*2))
+	// StabilityScore: prefer per-precision steady phases where each window runs a
+	// single kernel type so PowerCVPct is a genuine stability signal (not a
+	// workload-mix artifact). Fall back to combined steady using clock-only metrics
+	// when per-precision data is absent (older results, short profiles).
+	if len(gpu.PrecisionSteady) > 0 {
+		var sum float64
+		for _, p := range gpu.PrecisionSteady {
+			sum += clampScore(100 - (p.Steady.ClockCVPct*4 + p.Steady.PowerCVPct*2 + p.Steady.ClockDriftPct*2))
+		}
+		score.StabilityScore = sum / float64(len(gpu.PrecisionSteady))
+	} else {
+		score.StabilityScore = clampScore(100 - (gpu.Steady.ClockCVPct*4 + gpu.Steady.ClockDriftPct*2))
+	}
 	score.CompositeScore = compositeBenchmarkScore(score)
 	if gpu.MultiprocessorCount > 0 && gpu.Steady.AvgGraphicsClockMHz > 0 && score.ComputeScore > 0 {
 		score.TOPSPerSMPerGHz = score.ComputeScore / float64(gpu.MultiprocessorCount) / (gpu.Steady.AvgGraphicsClockMHz / 1000.0)
@@ -963,6 +1137,12 @@ func detectBenchmarkDegradationReasons(gpu BenchmarkGPUResult, normalizationStat
 	if normalizationStatus != "full" {
 		reasons = append(reasons, "normalization_partial")
 	}
+	if gpu.ECC.Uncorrected > 0 {
+		reasons = append(reasons, "ecc_uncorrected_errors")
+	}
+	if gpu.ECC.Corrected > 0 {
+		reasons = append(reasons, "ecc_corrected_errors")
+	}
 	return dedupeStrings(reasons)
 }
 
@@ -1064,6 +1244,36 @@ func diffThrottleCounters(before, after BenchmarkThrottleCounters) BenchmarkThro
 	}
 }
 
+func queryECCCounters(gpuIndex int) (BenchmarkECCCounters, error) {
+	out, err := satExecCommand(
+		"nvidia-smi",
+		"--id="+strconv.Itoa(gpuIndex),
+		"--query-gpu=ecc.errors.corrected.volatile.total,ecc.errors.uncorrected.volatile.total",
+		"--format=csv,noheader,nounits",
+	).Output()
+	if err != nil {
+		return BenchmarkECCCounters{}, err
+	}
+	fields := strings.Split(strings.TrimSpace(string(out)), ",")
+	if len(fields) < 2 {
+		return BenchmarkECCCounters{}, fmt.Errorf("unexpected ECC counter columns: %q", strings.TrimSpace(string(out)))
+	}
+	corrected, err1 := strconv.ParseUint(strings.TrimSpace(fields[0]), 10, 64)
+	uncorrected, err2 := strconv.ParseUint(strings.TrimSpace(fields[1]), 10, 64)
+	if err1 != nil || err2 != nil {
+		// ECC may be disabled on this GPU — return zero counters silently.
+		return BenchmarkECCCounters{}, nil
+	}
+	return BenchmarkECCCounters{Corrected: corrected, Uncorrected: uncorrected}, nil
+}
+
+func diffECCCounters(before, after BenchmarkECCCounters) BenchmarkECCCounters {
+	return BenchmarkECCCounters{
+		Corrected:   saturatingSub(after.Corrected, before.Corrected),
+		Uncorrected: saturatingSub(after.Uncorrected, before.Uncorrected),
+	}
+}
+
 func queryActiveComputeApps(gpuIndices []int) ([]string, error) {
 	args := []string{
 		"--query-compute-apps=gpu_uuid,pid,process_name",
@@ -1141,6 +1351,10 @@ func buildBenchmarkFindings(result NvidiaBenchmarkResult) []string {
 				findings = append(findings, fmt.Sprintf("GPU %d showed unstable clocks/power over the benchmark window.", gpu.Index))
 			case "normalization_partial":
 				findings = append(findings, fmt.Sprintf("GPU %d ran without full benchmark normalization.", gpu.Index))
+			case "ecc_uncorrected_errors":
+				findings = append(findings, fmt.Sprintf("GPU %d reported %d uncorrected ECC error(s) — possible hardware fault.", gpu.Index, gpu.ECC.Uncorrected))
+			case "ecc_corrected_errors":
+				findings = append(findings, fmt.Sprintf("GPU %d reported %d corrected ECC error(s) — possible DRAM degradation.", gpu.Index, gpu.ECC.Corrected))
 			}
 		}
 		if gpu.Backend == "driver-ptx" {
@@ -1387,7 +1601,10 @@ func maxInt(a, b int) int {
 // queryIPMIServerPowerW reads the current server power draw via ipmitool dcmi.
 // Returns 0 and an error if IPMI is unavailable or the output cannot be parsed.
 func queryIPMIServerPowerW() (float64, error) {
-	out, err := satExecCommand("ipmitool", "dcmi", "power", "reading").Output()
+	ctx, cancel := context.WithTimeout(context.Background(), 10*time.Second)
+	defer cancel()
+	cmd := exec.CommandContext(ctx, "ipmitool", "dcmi", "power", "reading")
+	out, err := cmd.Output()
 	if err != nil {
 		return 0, fmt.Errorf("ipmitool dcmi power reading: %w", err)
 	}
@@ -1406,6 +1623,7 @@ func sampleIPMIPowerSeries(ctx context.Context, durationSec int) (meanW float64,
 	}
 	deadline := time.Now().Add(time.Duration(durationSec) * time.Second)
 	var samples []float64
+loop:
 	for {
 		if w, err := queryIPMIServerPowerW(); err == nil {
 			samples = append(samples, w)
@@ -1415,7 +1633,7 @@ func sampleIPMIPowerSeries(ctx context.Context, durationSec int) (meanW float64,
 		}
 		select {
 		case <-ctx.Done():
-			break
+			break loop
 		case <-time.After(2 * time.Second):
 		}
 	}
@@ -1510,6 +1728,8 @@ func runNvidiaBenchmarkParallel(
 	calibPowerByIndex map[int]float64,
 	serverIdleW *float64, serverLoadedWSum *float64,
 	serverIdleOK *bool, serverLoadedOK *bool, serverLoadedSamples *int,
+	allMetricRows *[]GPUMetricRow,
+	gpuBurnLog string,
 ) {
 	allDevices := joinIndexList(selected)
 
@@ -1549,8 +1769,8 @@ func runNvidiaBenchmarkParallel(
 	for _, idx := range selected {
 		perGPU := filterRowsByGPU(baselineRows, idx)
 		gpuResults[idx].Baseline = summarizeBenchmarkTelemetry(perGPU)
-		writeBenchmarkMetricsFiles(runDir, fmt.Sprintf("gpu-%d-baseline", idx), perGPU)
 	}
+	appendBenchmarkMetrics(allMetricRows, baselineRows, "baseline")
 
 	// Sample server idle power once.
 	if !*serverIdleOK {
@@ -1569,31 +1789,86 @@ func runNvidiaBenchmarkParallel(
 		"--devices", allDevices,
 	}
 	logFunc(fmt.Sprintf("GPUs %s: parallel warmup (%ds)", allDevices, spec.WarmupSec))
-	warmupOut, warmupRows, warmupErr := runBenchmarkCommandWithMetrics(ctx, verboseLog, "gpu-all-warmup.log", warmupCmd, nil, selected, runDir, "gpu-all-warmup", logFunc)
-	_ = os.WriteFile(filepath.Join(runDir, "gpu-all-warmup.log"), warmupOut, 0644)
-	for _, idx := range selected {
-		writeBenchmarkMetricsFiles(runDir, fmt.Sprintf("gpu-%d-warmup", idx), filterRowsByGPU(warmupRows, idx))
-	}
+	warmupOut, warmupRows, warmupErr := runBenchmarkCommandWithMetrics(ctx, verboseLog, "gpu-all-warmup.log", warmupCmd, nil, selected, logFunc)
+	appendBenchmarkMetrics(allMetricRows, warmupRows, "warmup")
+	appendBenchmarkStageLog(gpuBurnLog, "bee-gpu-burn", "warmup", warmupOut)
 	if warmupErr != nil {
 		for _, idx := range selected {
 			gpuResults[idx].Notes = append(gpuResults[idx].Notes, "parallel warmup failed: "+warmupErr.Error())
 		}
 	}
 
+	// ── Per-precision stability phases (parallel) ─────────────────────────────
+	totalSlots := len(benchmarkPrecisionPhases) + 1
+	perPhaseSec := spec.SteadySec / totalSlots
+	if perPhaseSec < 60 {
+		perPhaseSec = 60
+	}
+	eccBase := make(map[int]BenchmarkECCCounters, len(selected))
+	for _, idx := range selected {
+		eccBase[idx], _ = queryECCCounters(idx)
+	}
+	for _, prec := range benchmarkPrecisionPhases {
+		phaseCmd := []string{
+			"bee-gpu-burn",
+			"--seconds", strconv.Itoa(perPhaseSec),
+			"--size-mb", strconv.Itoa(opts.SizeMB),
+			"--devices", allDevices,
+			"--precision", prec,
+		}
+		logFunc(fmt.Sprintf("GPUs %s: %s stability phase (%ds)", allDevices, prec, perPhaseSec))
+		phaseLogName := "gpu-all-steady-" + prec
+		eccBeforePhase := make(map[int]BenchmarkECCCounters, len(selected))
+		for _, idx := range selected {
+			eccBeforePhase[idx], _ = queryECCCounters(idx)
+		}
+		phaseOut, phaseRows, phaseErr := runBenchmarkCommandWithMetrics(ctx, verboseLog, phaseLogName+".log", phaseCmd, nil, selected, logFunc)
+		appendBenchmarkMetrics(allMetricRows, phaseRows, phaseLogName)
+		appendBenchmarkStageLog(gpuBurnLog, "bee-gpu-burn", phaseLogName, phaseOut)
+		eccAfterPhase := make(map[int]BenchmarkECCCounters, len(selected))
+		for _, idx := range selected {
+			eccAfterPhase[idx], _ = queryECCCounters(idx)
+		}
+		if phaseErr != nil || len(phaseRows) == 0 {
+			continue
+		}
+		parseByGPU := parseBenchmarkBurnLogByGPU(string(phaseOut))
+		for _, idx := range selected {
+			perGPU := filterRowsByGPU(phaseRows, idx)
+			if len(perGPU) == 0 {
+				continue
+			}
+			phase := BenchmarkPrecisionSteadyPhase{
+				Precision: prec,
+				Steady:    summarizeBenchmarkTelemetry(perGPU),
+				ECC:       diffECCCounters(eccBeforePhase[idx], eccAfterPhase[idx]),
+			}
+			if pr, ok := parseByGPU[idx]; ok {
+				for _, p := range pr.Profiles {
+					if p.Supported {
+						phase.TeraOpsPerSec += p.TeraOpsPerSec
+						phase.WeightedTeraOpsPerSec += p.WeightedTeraOpsPerSec
+					}
+				}
+			}
+			gpuResults[idx].PrecisionSteady = append(gpuResults[idx].PrecisionSteady, phase)
+		}
+	}
+
 	// Snapshot throttle counters before steady.
 	beforeThrottle := make(map[int]BenchmarkThrottleCounters, len(selected))
 	for _, idx := range selected {
 		beforeThrottle[idx], _ = queryThrottleCounters(idx)
 	}
 
-	// Steady: all GPUs simultaneously.
+	// Steady: all GPUs simultaneously (combined). Fixed at one slot = perPhaseSec.
 	steadyCmd := []string{
 		"bee-gpu-burn",
-		"--seconds", strconv.Itoa(spec.SteadySec),
+		"--seconds", strconv.Itoa(perPhaseSec),
 		"--size-mb", strconv.Itoa(opts.SizeMB),
 		"--devices", allDevices,
 	}
-	logFunc(fmt.Sprintf("GPUs %s: parallel steady compute (%ds)", allDevices, spec.SteadySec))
+	logFunc(fmt.Sprintf("GPUs %s: parallel steady compute (combined, %ds)", allDevices, perPhaseSec))
 
 	// Sample server power via IPMI in parallel with steady phase.
 	ipmiStopCh := make(chan struct{})
@@ -1627,7 +1902,9 @@ func runNvidiaBenchmarkParallel(
 		}
 	}()
 
-	steadyOut, steadyRows, steadyErr := runBenchmarkCommandWithMetrics(ctx, verboseLog, "gpu-all-steady.log", steadyCmd, nil, selected, runDir, "gpu-all-steady", logFunc)
+	steadyOut, steadyRows, steadyErr := runBenchmarkCommandWithMetrics(ctx, verboseLog, "gpu-all-steady.log", steadyCmd, nil, selected, logFunc)
+	appendBenchmarkMetrics(allMetricRows, steadyRows, "steady")
+	appendBenchmarkStageLog(gpuBurnLog, "bee-gpu-burn", "steady", steadyOut)
 	close(ipmiStopCh)
 	if loadedW, ok := <-ipmiResultCh; ok {
 		*serverLoadedWSum += loadedW
@@ -1635,8 +1912,6 @@ func runNvidiaBenchmarkParallel(
 		*serverLoadedOK = true
 		logFunc(fmt.Sprintf("GPUs %s: server loaded power (IPMI): %.0f W", allDevices, loadedW))
 	}
-	_ = os.WriteFile(filepath.Join(runDir, "gpu-all-steady.log"), steadyOut, 0644)
-
 	afterThrottle := make(map[int]BenchmarkThrottleCounters, len(selected))
 	for _, idx := range selected {
 		afterThrottle[idx], _ = queryThrottleCounters(idx)
@@ -1646,9 +1921,11 @@ func runNvidiaBenchmarkParallel(
 
 	for _, idx := range selected {
 		perGPU := filterRowsByGPU(steadyRows, idx)
-		writeBenchmarkMetricsFiles(runDir, fmt.Sprintf("gpu-%d-steady", idx), perGPU)
 		gpuResults[idx].Steady = summarizeBenchmarkTelemetry(perGPU)
 		gpuResults[idx].Throttle = diffThrottleCounters(beforeThrottle[idx], afterThrottle[idx])
+		if eccFinal, err := queryECCCounters(idx); err == nil {
+			gpuResults[idx].ECC = diffECCCounters(eccBase[idx], eccFinal)
+		}
 
 		if pr, ok := parseResults[idx]; ok {
 			gpuResults[idx].ComputeCapability = pr.ComputeCapability
@@ -1673,8 +1950,8 @@ func runNvidiaBenchmarkParallel(
 	for _, idx := range selected {
 		perGPU := filterRowsByGPU(cooldownRows, idx)
 		gpuResults[idx].Cooldown = summarizeBenchmarkTelemetry(perGPU)
-		writeBenchmarkMetricsFiles(runDir, fmt.Sprintf("gpu-%d-cooldown", idx), perGPU)
 	}
+	appendBenchmarkMetrics(allMetricRows, cooldownRows, "cooldown")
 
 	// Score and finalize each GPU.
 	for _, idx := range selected {
@@ -1884,7 +2161,7 @@ func runBenchmarkPowerCalibration(
 	logFunc(fmt.Sprintf("power calibration: running dcgmi targeted_power for %ds on GPUs %s", calibDurationSec, joinIndexList(gpuIndices)))
 
 	cmd := nvidiaDCGMNamedDiagCommand("targeted_power", calibDurationSec, gpuIndices)
-	out, rows, err := runBenchmarkCommandWithMetrics(ctx, verboseLog, "power-calibration.log", cmd, nil, gpuIndices, runDir, "power-calibration", logFunc)
+	out, rows, err := runBenchmarkCommandWithMetrics(ctx, verboseLog, "power-calibration.log", cmd, nil, gpuIndices, logFunc)
 	_ = os.WriteFile(filepath.Join(runDir, "power-calibration.log"), out, 0644)
 	if err != nil {
 		logFunc(fmt.Sprintf("power calibration: dcgmi targeted_power failed (%v), skipping", err))

audit/internal/platform/benchmark_report.go

@@ -2,25 +2,15 @@ package platform
 
 import (
 	"fmt"
-	"os"
-	"path/filepath"
-	"regexp"
 	"strings"
 	"time"
 )
 
 func renderBenchmarkReport(result NvidiaBenchmarkResult) string {
-	return renderBenchmarkReportWithCharts(result, nil)
+	return renderBenchmarkReportWithCharts(result)
 }
 
-type benchmarkReportChart struct {
-	Title   string
-	Content string
-}
-
-var ansiEscapePattern = regexp.MustCompile(`\x1b\[[0-9;]*m`)
-
-func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult, charts []benchmarkReportChart) string {
+func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult) string {
 	var b strings.Builder
 
 	// ── Header ────────────────────────────────────────────────────────────────
@@ -91,10 +81,28 @@ func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult, charts []benc
 		b.WriteString("\n")
 	}
 
+	// ── Methodology ───────────────────────────────────────────────────────────
+	b.WriteString("## Methodology\n\n")
+	fmt.Fprintf(&b, "- Profile `%s` uses standardized baseline -> warmup -> steady-state -> interconnect -> cooldown phases.\n", result.BenchmarkProfile)
+	b.WriteString("- Single-GPU compute score comes from `bee-gpu-burn` on the cuBLASLt path when available.\n")
+	b.WriteString("- Thermal and power limits are inferred from NVIDIA clock-event counters plus sustained telemetry.\n")
+	b.WriteString("- `result.json` is the canonical machine-readable source for the run.\n\n")
+	b.WriteString("**Compute score** is derived from two phases:\n\n")
+	b.WriteString("- **Synthetic** — each precision type (fp8, fp16, fp32, fp64, fp4) runs alone for a dedicated window. ")
+	b.WriteString("Measures peak throughput with the full GPU dedicated to one kernel type. ")
+	b.WriteString("Each result is normalised to fp32-equivalent TOPS using precision weights: ")
+	b.WriteString("fp64 ×2.0 · fp32 ×1.0 · fp16 ×0.5 · fp8 ×0.25 · fp4 ×0.125.\n")
+	b.WriteString("- **Mixed** — all precision types run simultaneously (combined phase). ")
+	b.WriteString("Reflects real inference workloads where fp8 matrix ops, fp16 attention and fp32 accumulation compete for bandwidth and SM scheduler slots.\n\n")
+	b.WriteString("**Formula:** `Compute = Synthetic × (1 + MixedEfficiency × 0.3)`\n\n")
+	b.WriteString("where `MixedEfficiency = Mixed / Synthetic`. A GPU that sustains 90 % throughput under mixed load ")
+	b.WriteString("receives a +27 % bonus over its synthetic score; one that drops to 60 % receives +18 %.\n\n")
+	b.WriteString("**Composite score** = `Compute × quality_factor` where quality factors in power sustain, thermal sustain, stability, and interconnect.\n\n")
+
 	// ── Scorecard table ───────────────────────────────────────────────────────
 	b.WriteString("## Scorecard\n\n")
-	b.WriteString("| GPU | Status | Composite | Compute | TOPS/SM/GHz | Power Sustain | Thermal Sustain | Stability | Interconnect |\n")
-	b.WriteString("|-----|--------|-----------|---------|-------------|---------------|-----------------|-----------|-------------|\n")
+	b.WriteString("| GPU | Status | Composite | Compute | Synthetic | Mixed | Mixed Eff. | TOPS/SM/GHz | Power Sustain | Thermal Sustain | Stability | Interconnect |\n")
+	b.WriteString("|-----|--------|-----------|---------|-----------|-------|------------|-------------|---------------|-----------------|-----------|-------------|\n")
 	for _, gpu := range result.GPUs {
 		name := strings.TrimSpace(gpu.Name)
 		if name == "" {
@@ -108,11 +116,26 @@ func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult, charts []benc
 		if gpu.Scores.TOPSPerSMPerGHz > 0 {
 			topsPerSM = fmt.Sprintf("%.3f", gpu.Scores.TOPSPerSMPerGHz)
 		}
-		fmt.Fprintf(&b, "| GPU %d %s | %s | **%.2f** | %.2f | %s | %.1f | %.1f | %.1f | %s |\n",
+		synthetic := "-"
+		if gpu.Scores.SyntheticScore > 0 {
+			synthetic = fmt.Sprintf("%.2f", gpu.Scores.SyntheticScore)
+		}
+		mixed := "-"
+		if gpu.Scores.MixedScore > 0 {
+			mixed = fmt.Sprintf("%.2f", gpu.Scores.MixedScore)
+		}
+		mixedEff := "-"
+		if gpu.Scores.MixedEfficiency > 0 {
+			mixedEff = fmt.Sprintf("%.1f%%", gpu.Scores.MixedEfficiency*100)
+		}
+		fmt.Fprintf(&b, "| GPU %d %s | %s | **%.2f** | %.2f | %s | %s | %s | %s | %.1f | %.1f | %.1f | %s |\n",
 			gpu.Index, name,
 			gpu.Status,
 			gpu.Scores.CompositeScore,
 			gpu.Scores.ComputeScore,
+			synthetic,
+			mixed,
+			mixedEff,
 			topsPerSM,
 			gpu.Scores.PowerSustainScore,
 			gpu.Scores.ThermalSustainScore,
@@ -162,6 +185,34 @@ func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult, charts []benc
 		fmt.Fprintf(&b, "| GPU utilisation | %.1f %% | — |\n", gpu.Steady.AvgUsagePct)
 		b.WriteString("\n")
 
+		// Per-precision stability phases.
+		if len(gpu.PrecisionSteady) > 0 {
+			b.WriteString("**Per-precision stability:**\n\n")
+			b.WriteString("| Precision | Clock CV | Power CV | Clock Drift | ECC corr | ECC uncorr |\n|-----------|----------|----------|-------------|----------|------------|\n")
+			for _, p := range gpu.PrecisionSteady {
+				eccCorr := "—"
+				eccUncorr := "—"
+				if !p.ECC.IsZero() {
+					eccCorr = fmt.Sprintf("%d", p.ECC.Corrected)
+					eccUncorr = fmt.Sprintf("%d", p.ECC.Uncorrected)
+				}
+				fmt.Fprintf(&b, "| %s | %.1f%% | %.1f%% | %.1f%% | %s | %s |\n",
+					p.Precision, p.Steady.ClockCVPct, p.Steady.PowerCVPct, p.Steady.ClockDriftPct,
+					eccCorr, eccUncorr)
+			}
+			b.WriteString("\n")
+		} else {
+			// Legacy: show combined-window variance.
+			fmt.Fprintf(&b, "**Clock/power variance (combined window):** clock CV %.1f%% · power CV %.1f%% · clock drift %.1f%%\n\n",
+				gpu.Steady.ClockCVPct, gpu.Steady.PowerCVPct, gpu.Steady.ClockDriftPct)
+		}
+
+		// ECC summary
+		if !gpu.ECC.IsZero() {
+			fmt.Fprintf(&b, "**ECC errors (total):** corrected=%d uncorrected=%d\n\n",
+				gpu.ECC.Corrected, gpu.ECC.Uncorrected)
+		}
+
 		// Throttle
 		throttle := formatThrottleLine(gpu.Throttle, gpu.Steady.DurationSec)
 		if throttle != "none" {
@@ -171,12 +222,14 @@ func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult, charts []benc
 		// Precision results
 		if len(gpu.PrecisionResults) > 0 {
 			b.WriteString("**Precision results:**\n\n")
-			b.WriteString("| Precision | TOPS | Lanes | Iterations |\n|-----------|------|-------|------------|\n")
+			b.WriteString("| Precision | TOPS (raw) | Weight | TOPS (fp32-eq) | Lanes | Iterations |\n|-----------|------------|--------|----------------|-------|------------|\n")
 			for _, p := range gpu.PrecisionResults {
 				if p.Supported {
-					fmt.Fprintf(&b, "| %s | %.2f | %d | %d |\n", p.Name, p.TeraOpsPerSec, p.Lanes, p.Iterations)
+					weightStr := fmt.Sprintf("×%.3g", p.Weight)
+					fmt.Fprintf(&b, "| %s | %.2f | %s | %.2f | %d | %d |\n",
+						p.Name, p.TeraOpsPerSec, weightStr, p.WeightedTeraOpsPerSec, p.Lanes, p.Iterations)
 				} else {
-					fmt.Fprintf(&b, "| %s | — (unsupported) | — | — |\n", p.Name)
+					fmt.Fprintf(&b, "| %s | — (unsupported) | — | — | — | — |\n", p.Name)
 				}
 			}
 			b.WriteString("\n")
@@ -237,61 +290,16 @@ func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult, charts []benc
 		}
 	}
 
-	// ── Terminal charts (steady-state only) ───────────────────────────────────
-	if len(charts) > 0 {
-		b.WriteString("## Steady-State Charts\n\n")
-		for _, chart := range charts {
-			content := strings.TrimSpace(stripANSIEscapeSequences(chart.Content))
-			if content == "" {
-				continue
-			}
-			fmt.Fprintf(&b, "### %s\n\n```\n%s\n```\n\n", chart.Title, content)
-		}
-	}
-
-	// ── Methodology ───────────────────────────────────────────────────────────
-	b.WriteString("## Methodology\n\n")
-	fmt.Fprintf(&b, "- Profile `%s` uses standardized baseline → warmup → steady-state → interconnect → cooldown phases.\n", result.BenchmarkProfile)
-	b.WriteString("- Single-GPU compute score from bee-gpu-burn cuBLASLt when available.\n")
-	b.WriteString("- Thermal and power limitations inferred from NVIDIA clock event reason counters and sustained telemetry.\n")
-	b.WriteString("- `result.json` is the canonical machine-readable source for this benchmark run.\n\n")
-
 	// ── Raw files ─────────────────────────────────────────────────────────────
 	b.WriteString("## Raw Files\n\n")
 	b.WriteString("- `result.json`\n- `report.md`\n- `summary.txt`\n- `verbose.log`\n")
-	b.WriteString("- `gpu-*-baseline-metrics.csv/html/term.txt`\n")
-	b.WriteString("- `gpu-*-warmup.log`\n")
-	b.WriteString("- `gpu-*-steady.log`\n")
-	b.WriteString("- `gpu-*-steady-metrics.csv/html/term.txt`\n")
-	b.WriteString("- `gpu-*-cooldown-metrics.csv/html/term.txt`\n")
+	b.WriteString("- `gpu-metrics.csv`\n- `gpu-metrics.html`\n- `gpu-burn.log`\n")
 	if result.Interconnect != nil {
 		b.WriteString("- `nccl-all-reduce.log`\n")
 	}
 	return b.String()
 }
 
-// loadBenchmarkReportCharts loads only steady-state terminal charts (baseline and
-// cooldown charts are not useful for human review).
-func loadBenchmarkReportCharts(runDir string, gpuIndices []int) []benchmarkReportChart {
-	var charts []benchmarkReportChart
-	for _, idx := range gpuIndices {
-		path := filepath.Join(runDir, fmt.Sprintf("gpu-%d-steady-metrics-term.txt", idx))
-		raw, err := os.ReadFile(path)
-		if err != nil || len(raw) == 0 {
-			continue
-		}
-		charts = append(charts, benchmarkReportChart{
-			Title:   fmt.Sprintf("GPU %d — Steady State", idx),
-			Content: string(raw),
-		})
-	}
-	return charts
-}
-
-func stripANSIEscapeSequences(raw string) string {
-	return ansiEscapePattern.ReplaceAllString(raw, "")
-}
-
 // formatThrottleLine renders throttle counters as human-readable percentages of
 // the steady-state window.  Only non-zero counters are shown.  When the steady
 // duration is unknown (0), raw seconds are shown instead.

audit/internal/platform/benchmark_test.go

@@ -147,36 +147,27 @@ func TestRenderBenchmarkReportIncludesFindingsAndScores(t *testing.T) {
 	}
 }
 
-func TestRenderBenchmarkReportIncludesTerminalChartsWithoutANSI(t *testing.T) {
+func TestRenderBenchmarkReportListsUnifiedArtifacts(t *testing.T) {
 	t.Parallel()
 
-	report := renderBenchmarkReportWithCharts(NvidiaBenchmarkResult{
+	report := renderBenchmarkReport(NvidiaBenchmarkResult{
 		BenchmarkProfile:   NvidiaBenchmarkProfileStandard,
 		OverallStatus:      "OK",
 		SelectedGPUIndices: []int{0},
 		Normalization: BenchmarkNormalization{
 			Status: "full",
 		},
-	}, []benchmarkReportChart{
-		{
-			Title:   "GPU 0 Steady State",
-			Content: "\x1b[31mGPU 0 chart\x1b[0m\n 42┤───",
-		},
 	})
 
 	for _, needle := range []string{
-		"Steady-State Charts",
-		"GPU 0 Steady State",
-		"GPU 0 chart",
-		"42┤───",
+		"gpu-metrics.csv",
+		"gpu-metrics.html",
+		"gpu-burn.log",
 	} {
 		if !strings.Contains(report, needle) {
 			t.Fatalf("report missing %q\n%s", needle, report)
 		}
 	}
-	if strings.Contains(report, "\x1b[31m") {
-		t.Fatalf("report should not contain ANSI escapes\n%s", report)
-	}
 }
 
 func TestEnrichGPUInfoWithMaxClocks(t *testing.T) {

audit/internal/platform/benchmark_types.go

@@ -43,7 +43,6 @@ type NvidiaBenchmarkOptions struct {
 	RampRunID         string // shared identifier across all steps of the same ramp-up run
 }
 
-
 type NvidiaBenchmarkResult struct {
 	BenchmarkVersion   string                       `json:"benchmark_version"`
 	GeneratedAt        time.Time                    `json:"generated_at"`
@@ -107,8 +106,11 @@ type BenchmarkGPUResult struct {
 	LockedMemoryClockMHz   float64                         `json:"locked_memory_clock_mhz,omitempty"`
 	Baseline               BenchmarkTelemetrySummary       `json:"baseline"`
 	Steady                 BenchmarkTelemetrySummary       `json:"steady"`
+	PrecisionSteady        []BenchmarkPrecisionSteadyPhase `json:"precision_steady,omitempty"`
 	Cooldown               BenchmarkTelemetrySummary       `json:"cooldown"`
 	Throttle               BenchmarkThrottleCounters       `json:"throttle_counters"`
+	// ECC error delta accumulated over the full benchmark (all phases combined).
+	ECC                BenchmarkECCCounters       `json:"ecc,omitempty"`
 	PrecisionResults   []BenchmarkPrecisionResult `json:"precision_results,omitempty"`
 	Scores             BenchmarkScorecard         `json:"scores"`
 	DegradationReasons []string                   `json:"degradation_reasons,omitempty"`
@@ -142,6 +144,18 @@ type BenchmarkThrottleCounters struct {
 	HWPowerBrakeSlowdownUS uint64 `json:"hw_power_brake_slowdown_us"`
 }
 
+// BenchmarkECCCounters holds ECC error counts sampled at a point in time.
+// Corrected = single-bit errors fixed by ECC (DRAM degradation).
+// Uncorrected = double-bit errors that could not be corrected (serious fault).
+// Both are volatile (since last driver reset), not persistent.
+type BenchmarkECCCounters struct {
+	Corrected   uint64 `json:"corrected"`
+	Uncorrected uint64 `json:"uncorrected"`
+}
+
+func (e BenchmarkECCCounters) Total() uint64 { return e.Corrected + e.Uncorrected }
+func (e BenchmarkECCCounters) IsZero() bool  { return e.Corrected == 0 && e.Uncorrected == 0 }
+
 type BenchmarkPrecisionResult struct {
 	Name          string  `json:"name"`
 	Category      string  `json:"category"`
@@ -152,19 +166,31 @@ type BenchmarkPrecisionResult struct {
 	K             uint64  `json:"k,omitempty"`
 	Iterations    uint64  `json:"iterations,omitempty"`
 	TeraOpsPerSec float64 `json:"teraops_per_sec,omitempty"`
+	// Weight is the fp32-equivalence factor for this precision category.
+	// fp32 = 1.0 (baseline), fp64 = 2.0, fp16 = 0.5, fp8 = 0.25, fp4 = 0.125.
+	// WeightedTOPS = TeraOpsPerSec * Weight gives fp32-equivalent throughput.
+	Weight                float64 `json:"weight,omitempty"`
+	WeightedTeraOpsPerSec float64 `json:"weighted_teraops_per_sec,omitempty"`
 	Notes                 string  `json:"notes,omitempty"`
 }
 
 type BenchmarkScorecard struct {
 	ComputeScore float64 `json:"compute_score"`
+	// SyntheticScore is the sum of fp32-equivalent TOPS from per-precision
+	// steady phases (each precision ran alone, full GPU dedicated).
+	SyntheticScore float64 `json:"synthetic_score,omitempty"`
+	// MixedScore is the sum of fp32-equivalent TOPS from the combined phase
+	// (all precisions competing simultaneously — closer to real workloads).
+	MixedScore float64 `json:"mixed_score,omitempty"`
+	// MixedEfficiency = MixedScore / SyntheticScore. Measures how well the GPU
+	// sustains throughput under concurrent mixed-precision load.
+	MixedEfficiency     float64 `json:"mixed_efficiency,omitempty"`
 	PowerSustainScore   float64 `json:"power_sustain_score"`
 	ThermalSustainScore float64 `json:"thermal_sustain_score"`
 	StabilityScore      float64 `json:"stability_score"`
 	InterconnectScore   float64 `json:"interconnect_score"`
 	CompositeScore      float64 `json:"composite_score"`
 	// TOPSPerSMPerGHz is compute efficiency independent of clock speed and SM count.
-	// Comparable across throttle levels and GPU generations. Low value at normal
-	// clocks indicates silicon degradation.
 	TOPSPerSMPerGHz float64 `json:"tops_per_sm_per_ghz,omitempty"`
 }
 
@@ -182,6 +208,20 @@ type BenchmarkServerPower struct {
 	Notes           []string `json:"notes,omitempty"`
 }
 
+// BenchmarkPrecisionSteadyPhase holds per-precision-category telemetry collected
+// during a dedicated single-precision steady window.  Because only one kernel
+// type runs at a time the PowerCVPct here is a genuine stability signal.
+type BenchmarkPrecisionSteadyPhase struct {
+	Precision             string                    `json:"precision"` // e.g. "fp8", "fp16", "fp32"
+	Steady                BenchmarkTelemetrySummary `json:"steady"`
+	TeraOpsPerSec         float64                   `json:"teraops_per_sec,omitempty"`
+	WeightedTeraOpsPerSec float64                   `json:"weighted_teraops_per_sec,omitempty"`
+	// ECC errors accumulated during this precision phase only.
+	// Non-zero corrected = stress-induced DRAM errors for this kernel type.
+	// Any uncorrected = serious fault triggered by this precision workload.
+	ECC BenchmarkECCCounters `json:"ecc,omitempty"`
+}
+
 type BenchmarkInterconnectResult struct {
 	Status             string   `json:"status"`
 	Attempted          bool     `json:"attempted"`

audit/internal/platform/gpu_metrics.go

@@ -13,6 +13,7 @@ import (
 
 // GPUMetricRow is one telemetry sample from nvidia-smi during a stress test.
 type GPUMetricRow struct {
+	Stage       string  `json:"stage,omitempty"`
 	ElapsedSec  float64 `json:"elapsed_sec"`
 	GPUIndex    int     `json:"index"`
 	TempC       float64 `json:"temp_c"`
@@ -141,14 +142,20 @@ func sampleAMDGPUMetrics() ([]GPUMetricRow, error) {
 // WriteGPUMetricsCSV writes collected rows as a CSV file.
 func WriteGPUMetricsCSV(path string, rows []GPUMetricRow) error {
 	var b bytes.Buffer
-	b.WriteString("elapsed_sec,gpu_index,temperature_c,usage_pct,mem_usage_pct,power_w,clock_mhz,mem_clock_mhz\n")
+	b.WriteString("stage,elapsed_sec,gpu_index,temperature_c,usage_pct,mem_usage_pct,power_w,clock_mhz,mem_clock_mhz\n")
 	for _, r := range rows {
-		fmt.Fprintf(&b, "%.1f,%d,%.1f,%.1f,%.1f,%.1f,%.0f,%.0f\n",
-			r.ElapsedSec, r.GPUIndex, r.TempC, r.UsagePct, r.MemUsagePct, r.PowerW, r.ClockMHz, r.MemClockMHz)
+		fmt.Fprintf(&b, "%s,%.1f,%d,%.1f,%.1f,%.1f,%.1f,%.0f,%.0f\n",
+			strconv.Quote(strings.TrimSpace(r.Stage)), r.ElapsedSec, r.GPUIndex, r.TempC, r.UsagePct, r.MemUsagePct, r.PowerW, r.ClockMHz, r.MemClockMHz)
 	}
 	return os.WriteFile(path, b.Bytes(), 0644)
 }
 
+type gpuMetricStageSpan struct {
+	Name  string
+	Start float64
+	End   float64
+}
+
 // WriteGPUMetricsHTML writes a standalone HTML file with one SVG chart per GPU.
 func WriteGPUMetricsHTML(path string, rows []GPUMetricRow) error {
 	// Group by GPU index preserving order.
@@ -163,9 +170,25 @@ func WriteGPUMetricsHTML(path string, rows []GPUMetricRow) error {
 		gpuMap[r.GPUIndex] = append(gpuMap[r.GPUIndex], r)
 	}
 
+	stageSpans := buildGPUMetricStageSpans(rows)
+	stageColorByName := make(map[string]string, len(stageSpans))
+	for i, span := range stageSpans {
+		stageColorByName[span.Name] = gpuMetricStagePalette[i%len(gpuMetricStagePalette)]
+	}
+
+	var legend strings.Builder
+	if len(stageSpans) > 0 {
+		legend.WriteString(`<div class="stage-legend">`)
+		for _, span := range stageSpans {
+			fmt.Fprintf(&legend, `<span class="stage-chip"><span class="stage-swatch" style="background:%s"></span>%s</span>`,
+				stageColorByName[span.Name], gpuHTMLEscape(span.Name))
+		}
+		legend.WriteString(`</div>`)
+	}
+
 	var svgs strings.Builder
 	for _, gpuIdx := range order {
-		svgs.WriteString(drawGPUChartSVG(gpuMap[gpuIdx], gpuIdx))
+		svgs.WriteString(drawGPUChartSVG(gpuMap[gpuIdx], gpuIdx, stageSpans, stageColorByName))
 		svgs.WriteString("\n")
 	}
 
@@ -175,21 +198,39 @@ func WriteGPUMetricsHTML(path string, rows []GPUMetricRow) error {
 <meta charset="utf-8">
 <title>GPU Stress Test Metrics</title>
 <style>
-body { font-family: sans-serif; background: #f0f0f0; margin: 0; padding: 20px; }
-h1 { text-align: center; color: #333; margin: 0 0 8px; }
-p  { text-align: center; color: #888; font-size: 13px; margin: 0 0 24px; }
+:root{--bg:#fff;--surface:#fff;--surface-2:#f9fafb;--border:rgba(34,36,38,.15);--border-lite:rgba(34,36,38,.1);--ink:rgba(0,0,0,.87);--muted:rgba(0,0,0,.6)}
+*{box-sizing:border-box}
+body{font:14px/1.5 Lato,"Helvetica Neue",Arial,Helvetica,sans-serif;background:var(--bg);color:var(--ink);margin:0}
+.page{padding:24px}
+.card{background:var(--surface);border:1px solid var(--border);border-radius:4px;box-shadow:0 1px 2px rgba(34,36,38,.15);overflow:hidden}
+.card-head{padding:11px 16px;background:var(--surface-2);border-bottom:1px solid var(--border);font-weight:700;font-size:13px}
+.card-body{padding:16px}
+h1{font-size:22px;margin:0 0 6px}
+p{color:var(--muted);font-size:13px;margin:0 0 16px}
+.stage-legend{display:flex;flex-wrap:wrap;gap:10px;margin:0 0 16px}
+.stage-chip{display:inline-flex;align-items:center;gap:8px;padding:4px 10px;border-radius:999px;background:var(--surface-2);border:1px solid var(--border-lite);font-size:12px}
+.stage-swatch{display:inline-block;width:12px;height:12px;border-radius:999px}
+.chart-block{margin-top:16px}
 </style>
 </head><body>
+<div class="page">
+<div class="card">
+<div class="card-head">GPU Stress Test Metrics</div>
+<div class="card-body">
 <h1>GPU Stress Test Metrics</h1>
 <p>Generated %s</p>
 %s
-</body></html>`, ts, svgs.String())
+<div class="chart-block">%s</div>
+</div>
+</div>
+</div>
+</body></html>`, ts, legend.String(), svgs.String())
 
 	return os.WriteFile(path, []byte(html), 0644)
 }
 
 // drawGPUChartSVG generates a self-contained SVG chart for one GPU.
-func drawGPUChartSVG(rows []GPUMetricRow, gpuIdx int) string {
+func drawGPUChartSVG(rows []GPUMetricRow, gpuIdx int, stageSpans []gpuMetricStageSpan, stageColorByName map[string]string) string {
 	// Layout
 	const W, H = 960, 520
 	const plotX1 = 120 // usage axis / chart left border
@@ -284,6 +325,23 @@ func drawGPUChartSVG(rows []GPUMetricRow, gpuIdx int) string {
 	}
 	b.WriteString("</g>\n")
 
+	// Stage backgrounds
+	for _, span := range stageSpans {
+		x1 := xv(span.Start)
+		x2 := xv(span.End)
+		if x2 < x1 {
+			x1, x2 = x2, x1
+		}
+		if x2-x1 < 1 {
+			x2 = x1 + 1
+		}
+		color := stageColorByName[span.Name]
+		fmt.Fprintf(&b, `<rect x="%.1f" y="%d" width="%.1f" height="%d" fill="%s" fill-opacity="0.18"/>`+"\n",
+			x1, plotY1, x2-x1, PH, color)
+		fmt.Fprintf(&b, `<text x="%.1f" y="%d" font-family="sans-serif" font-size="10" fill="#444" text-anchor="middle">%s</text>`+"\n",
+			x1+(x2-x1)/2, plotY1+12, gpuHTMLEscape(span.Name))
+	}
+
 	// Chart border
 	fmt.Fprintf(&b, `<rect x="%d" y="%d" width="%d" height="%d"`+
 		` fill="none" stroke="#333" stroke-width="1"/>`+"\n",
@@ -382,221 +440,6 @@ func drawGPUChartSVG(rows []GPUMetricRow, gpuIdx int) string {
 	return b.String()
 }
 
-const (
-	ansiAmber  = "\033[38;5;214m"
-	ansiReset  = "\033[0m"
-)
-
-const (
-	termChartWidth  = 70
-	termChartHeight = 12
-)
-
-// RenderGPUTerminalChart returns ANSI line charts (asciigraph-style) per GPU.
-// Used in SAT stress-test logs.
-func RenderGPUTerminalChart(rows []GPUMetricRow) string {
-	seen := make(map[int]bool)
-	var order []int
-	gpuMap := make(map[int][]GPUMetricRow)
-	for _, r := range rows {
-		if !seen[r.GPUIndex] {
-			seen[r.GPUIndex] = true
-			order = append(order, r.GPUIndex)
-		}
-		gpuMap[r.GPUIndex] = append(gpuMap[r.GPUIndex], r)
-	}
-
-	type seriesDef struct {
-		caption string
-		color   string
-		fn      func(GPUMetricRow) float64
-	}
-	defs := []seriesDef{
-		{"Temperature (°C)", ansiAmber, func(r GPUMetricRow) float64 { return r.TempC }},
-		{"GPU Usage (%)", ansiAmber, func(r GPUMetricRow) float64 { return r.UsagePct }},
-		{"Power (W)", ansiAmber, func(r GPUMetricRow) float64 { return r.PowerW }},
-		{"Clock (MHz)", ansiAmber, func(r GPUMetricRow) float64 { return r.ClockMHz }},
-	}
-
-	var b strings.Builder
-	for _, gpuIdx := range order {
-		gr := gpuMap[gpuIdx]
-		if len(gr) == 0 {
-			continue
-		}
-		tMax := gr[len(gr)-1].ElapsedSec - gr[0].ElapsedSec
-		fmt.Fprintf(&b, "GPU %d — Stress Test Metrics  (%.0f seconds)\n\n", gpuIdx, tMax)
-		for _, d := range defs {
-			b.WriteString(renderLineChart(extractGPUField(gr, d.fn), d.color, d.caption,
-				termChartHeight, termChartWidth))
-			b.WriteRune('\n')
-		}
-	}
-
-	return strings.TrimRight(b.String(), "\n")
-}
-
-// renderLineChart draws a single time-series line chart using box-drawing characters.
-// Produces output in the style of asciigraph: ╭─╮ │ ╰─╯ with a Y axis and caption.
-func renderLineChart(vals []float64, color, caption string, height, width int) string {
-	if len(vals) == 0 {
-		return caption + "\n"
-	}
-
-	mn, mx := gpuMinMax(vals)
-	if mn == mx {
-		mx = mn + 1
-	}
-
-	// Use the smaller of width or len(vals) to avoid stretching sparse data.
-	w := width
-	if len(vals) < w {
-		w = len(vals)
-	}
-	data := gpuDownsample(vals, w)
-
-	// row[i] = display row index: 0 = top = max value, height = bottom = min value.
-	row := make([]int, w)
-	for i, v := range data {
-		r := int(math.Round((mx - v) / (mx - mn) * float64(height)))
-		if r < 0 {
-			r = 0
-		}
-		if r > height {
-			r = height
-		}
-		row[i] = r
-	}
-
-	// Fill the character grid.
-	grid := make([][]rune, height+1)
-	for i := range grid {
-		grid[i] = make([]rune, w)
-		for j := range grid[i] {
-			grid[i][j] = ' '
-		}
-	}
-	for x := 0; x < w; x++ {
-		r := row[x]
-		if x == 0 {
-			grid[r][0] = '─'
-			continue
-		}
-		p := row[x-1]
-		switch {
-		case r == p:
-			grid[r][x] = '─'
-		case r < p: // value went up (row index decreased toward top)
-			grid[r][x] = '╭'
-			grid[p][x] = '╯'
-			for y := r + 1; y < p; y++ {
-				grid[y][x] = '│'
-			}
-		default: // r > p, value went down
-			grid[p][x] = '╮'
-			grid[r][x] = '╰'
-			for y := p + 1; y < r; y++ {
-				grid[y][x] = '│'
-			}
-		}
-	}
-
-	// Y axis tick labels.
-	ticks := gpuNiceTicks(mn, mx, height/2)
-	tickAtRow := make(map[int]string)
-	labelWidth := 4
-	for _, t := range ticks {
-		r := int(math.Round((mx - t) / (mx - mn) * float64(height)))
-		if r < 0 || r > height {
-			continue
-		}
-		s := gpuFormatTick(t)
-		tickAtRow[r] = s
-		if len(s) > labelWidth {
-			labelWidth = len(s)
-		}
-	}
-
-	var b strings.Builder
-	for r := 0; r <= height; r++ {
-		label := tickAtRow[r]
-		fmt.Fprintf(&b, "%*s", labelWidth, label)
-		switch {
-		case label != "":
-			b.WriteRune('┤')
-		case r == height:
-			b.WriteRune('┼')
-		default:
-			b.WriteRune('│')
-		}
-		b.WriteString(color)
-		b.WriteString(string(grid[r]))
-		b.WriteString(ansiReset)
-		b.WriteRune('\n')
-	}
-
-	// Bottom axis.
-	b.WriteString(strings.Repeat(" ", labelWidth))
-	b.WriteRune('└')
-	b.WriteString(strings.Repeat("─", w))
-	b.WriteRune('\n')
-
-	// Caption centered under the chart.
-	if caption != "" {
-		total := labelWidth + 1 + w
-		if pad := (total - len(caption)) / 2; pad > 0 {
-			b.WriteString(strings.Repeat(" ", pad))
-		}
-		b.WriteString(caption)
-		b.WriteRune('\n')
-	}
-
-	return b.String()
-}
-
-func extractGPUField(rows []GPUMetricRow, fn func(GPUMetricRow) float64) []float64 {
-	v := make([]float64, len(rows))
-	for i, r := range rows {
-		v[i] = fn(r)
-	}
-	return v
-}
-
-// gpuDownsample averages vals into w buckets (or nearest-neighbor upsamples if len(vals) < w).
-func gpuDownsample(vals []float64, w int) []float64 {
-	n := len(vals)
-	if n == 0 {
-		return make([]float64, w)
-	}
-	result := make([]float64, w)
-	if n >= w {
-		counts := make([]int, w)
-		for i, v := range vals {
-			bucket := i * w / n
-			if bucket >= w {
-				bucket = w - 1
-			}
-			result[bucket] += v
-			counts[bucket]++
-		}
-		for i := range result {
-			if counts[i] > 0 {
-				result[i] /= float64(counts[i])
-			}
-		}
-	} else {
-		// Nearest-neighbour upsample.
-		for i := range result {
-			src := i * (n - 1) / (w - 1)
-			if src >= n {
-				src = n - 1
-			}
-			result[i] = vals[src]
-		}
-	}
-	return result
-}
-
 func gpuMinMax(vals []float64) (float64, float64) {
 	if len(vals) == 0 {
 		return 0, 1
@@ -641,3 +484,46 @@ func gpuFormatTick(v float64) string {
 	}
 	return strconv.FormatFloat(v, 'f', 1, 64)
 }
+
+var gpuMetricStagePalette = []string{
+	"#d95c5c",
+	"#2185d0",
+	"#21ba45",
+	"#f2c037",
+	"#6435c9",
+	"#00b5ad",
+	"#a5673f",
+}
+
+func buildGPUMetricStageSpans(rows []GPUMetricRow) []gpuMetricStageSpan {
+	var spans []gpuMetricStageSpan
+	for _, row := range rows {
+		name := strings.TrimSpace(row.Stage)
+		if name == "" {
+			name = "run"
+		}
+		if len(spans) == 0 || spans[len(spans)-1].Name != name {
+			spans = append(spans, gpuMetricStageSpan{Name: name, Start: row.ElapsedSec, End: row.ElapsedSec})
+			continue
+		}
+		spans[len(spans)-1].End = row.ElapsedSec
+	}
+	for i := range spans {
+		if spans[i].End <= spans[i].Start {
+			spans[i].End = spans[i].Start + 1
+		}
+	}
+	return spans
+}
+
+var gpuHTMLReplacer = strings.NewReplacer(
+	"&", "&amp;",
+	"<", "&lt;",
+	">", "&gt;",
+	`"`, "&quot;",
+	"'", "&#39;",
+)
+
+func gpuHTMLEscape(s string) string {
+	return gpuHTMLReplacer.Replace(s)
+}

audit/internal/platform/gpu_metrics_test.go

@@ -0,0 +1,65 @@
+package platform
+
+import (
+	"os"
+	"path/filepath"
+	"strings"
+	"testing"
+)
+
+func TestWriteGPUMetricsCSVIncludesStageColumn(t *testing.T) {
+	t.Parallel()
+
+	dir := t.TempDir()
+	path := filepath.Join(dir, "gpu-metrics.csv")
+	rows := []GPUMetricRow{
+		{Stage: "warmup", ElapsedSec: 1, GPUIndex: 0, TempC: 71, UsagePct: 99, MemUsagePct: 80, PowerW: 420, ClockMHz: 1800, MemClockMHz: 1200},
+	}
+	if err := WriteGPUMetricsCSV(path, rows); err != nil {
+		t.Fatalf("WriteGPUMetricsCSV: %v", err)
+	}
+	raw, err := os.ReadFile(path)
+	if err != nil {
+		t.Fatalf("ReadFile: %v", err)
+	}
+	text := string(raw)
+	for _, needle := range []string{
+		"stage,elapsed_sec,gpu_index",
+		`"warmup",1.0,0,71.0,99.0,80.0,420.0,1800,1200`,
+	} {
+		if !strings.Contains(text, needle) {
+			t.Fatalf("csv missing %q\n%s", needle, text)
+		}
+	}
+}
+
+func TestWriteGPUMetricsHTMLShowsStageLegendAndLabels(t *testing.T) {
+	t.Parallel()
+
+	dir := t.TempDir()
+	path := filepath.Join(dir, "gpu-metrics.html")
+	rows := []GPUMetricRow{
+		{Stage: "baseline", ElapsedSec: 1, GPUIndex: 0, TempC: 50, UsagePct: 10, MemUsagePct: 5, PowerW: 100, ClockMHz: 500, MemClockMHz: 400},
+		{Stage: "baseline", ElapsedSec: 2, GPUIndex: 0, TempC: 51, UsagePct: 11, MemUsagePct: 5, PowerW: 101, ClockMHz: 510, MemClockMHz: 400},
+		{Stage: "steady-fp16", ElapsedSec: 3, GPUIndex: 0, TempC: 70, UsagePct: 98, MemUsagePct: 75, PowerW: 390, ClockMHz: 1700, MemClockMHz: 1100},
+		{Stage: "steady-fp16", ElapsedSec: 4, GPUIndex: 0, TempC: 71, UsagePct: 99, MemUsagePct: 76, PowerW: 395, ClockMHz: 1710, MemClockMHz: 1110},
+	}
+	if err := WriteGPUMetricsHTML(path, rows); err != nil {
+		t.Fatalf("WriteGPUMetricsHTML: %v", err)
+	}
+	raw, err := os.ReadFile(path)
+	if err != nil {
+		t.Fatalf("ReadFile: %v", err)
+	}
+	text := string(raw)
+	for _, needle := range []string{
+		"stage-legend",
+		"baseline",
+		"steady-fp16",
+		"GPU Stress Test Metrics",
+	} {
+		if !strings.Contains(text, needle) {
+			t.Fatalf("html missing %q\n%s", needle, text)
+		}
+	}
+}

audit/internal/platform/sat.go

@@ -1382,8 +1382,6 @@ func runSATCommandWithMetrics(ctx context.Context, verboseLog, name string, cmd
 	if len(metricRows) > 0 {
 		_ = WriteGPUMetricsCSV(filepath.Join(runDir, "gpu-metrics.csv"), metricRows)
 		_ = WriteGPUMetricsHTML(filepath.Join(runDir, "gpu-metrics.html"), metricRows)
-		chart := RenderGPUTerminalChart(metricRows)
-		_ = os.WriteFile(filepath.Join(runDir, "gpu-metrics-term.txt"), []byte(chart), 0644)
 	}
 
 	return out, err

audit/internal/webui/api.go

@@ -497,6 +497,7 @@ func (h *handler) handleAPISATRun(target string) http.HandlerFunc {
 				GPUIndices         []int    `json:"gpu_indices"`
 				ExcludeGPUIndices  []int    `json:"exclude_gpu_indices"`
 				StaggerGPUStart    bool     `json:"stagger_gpu_start"`
+				ParallelGPUs       bool     `json:"parallel_gpus"`
 				Loader             string   `json:"loader"`
 			Profile            string   `json:"profile"`
 			DisplayName        string   `json:"display_name"`
@@ -519,6 +520,7 @@ func (h *handler) handleAPISATRun(target string) http.HandlerFunc {
 				GPUIndices:         body.GPUIndices,
 				ExcludeGPUIndices:  body.ExcludeGPUIndices,
 				StaggerGPUStart:    body.StaggerGPUStart,
+				ParallelGPUs:       body.ParallelGPUs,
 				Loader:             body.Loader,
 			BurnProfile:        body.Profile,
 			DisplayName:        body.DisplayName,

audit/internal/webui/pages.go

@@ -1928,23 +1928,10 @@ func renderSATCard(id, label, runAction, headerActions, body string) string {
 
 // ── Benchmark ─────────────────────────────────────────────────────────────────
 
-type benchmarkHistoryColumn struct {
-	key      string
-	label    string
-	name     string
-	index    int
-	parallel bool
-}
-
-type benchmarkHistoryCell struct {
-	score   float64
-	present bool
-}
-
 type benchmarkHistoryRun struct {
 	generatedAt time.Time
 	displayTime string
-	cells       map[string]benchmarkHistoryCell
+	gpuScores   map[int]float64 // GPU index → composite score
 }
 
 func renderBenchmark(opts HandlerOptions) string {
@@ -2206,17 +2193,17 @@ benchmarkLoadGPUs();
 }
 
 func renderBenchmarkResultsCard(exportDir string) string {
-	columns, runs := loadBenchmarkHistory(exportDir)
+	maxIdx, runs := loadBenchmarkHistory(exportDir)
 	return renderBenchmarkResultsCardFromRuns(
 		"Benchmark Results",
 		"Composite score by saved benchmark run and GPU.",
 		"No saved benchmark runs yet.",
-		columns,
+		maxIdx,
 		runs,
 	)
 }
 
-func renderBenchmarkResultsCardFromRuns(title, description, emptyMessage string, columns []benchmarkHistoryColumn, runs []benchmarkHistoryRun) string {
+func renderBenchmarkResultsCardFromRuns(title, description, emptyMessage string, maxGPUIndex int, runs []benchmarkHistoryRun) string {
 	if len(runs) == 0 {
 		return `<div class="card"><div class="card-head">` + html.EscapeString(title) + `</div><div class="card-body"><p style="color:var(--muted);font-size:13px">` + html.EscapeString(emptyMessage) + `</p></div></div>`
 	}
@@ -2226,22 +2213,22 @@ func renderBenchmarkResultsCardFromRuns(title, description, emptyMessage string,
 		b.WriteString(`<p style="color:var(--muted);font-size:13px;margin-bottom:12px">` + html.EscapeString(description) + `</p>`)
 	}
 	b.WriteString(`<div style="overflow-x:auto">`)
-	b.WriteString(`<table><thead><tr><th>Test</th><th>Time</th>`)
-	for _, col := range columns {
-		b.WriteString(`<th>` + html.EscapeString(col.label) + `</th>`)
+	b.WriteString(`<table><thead><tr><th>Run</th><th>Time</th>`)
+	for i := 0; i <= maxGPUIndex; i++ {
+		b.WriteString(`<th>GPU ` + strconv.Itoa(i) + `</th>`)
 	}
 	b.WriteString(`</tr></thead><tbody>`)
 	for i, run := range runs {
 		b.WriteString(`<tr>`)
 		b.WriteString(`<td>#` + strconv.Itoa(i+1) + `</td>`)
 		b.WriteString(`<td>` + html.EscapeString(run.displayTime) + `</td>`)
-		for _, col := range columns {
-			cell, ok := run.cells[col.key]
-			if !ok || !cell.present {
+		for idx := 0; idx <= maxGPUIndex; idx++ {
+			score, ok := run.gpuScores[idx]
+			if !ok {
 				b.WriteString(`<td style="color:var(--muted)">-</td>`)
 				continue
 			}
-			b.WriteString(`<td>` + fmt.Sprintf("%.2f", cell.score) + `</td>`)
+			b.WriteString(`<td>` + fmt.Sprintf("%.2f", score) + `</td>`)
 		}
 		b.WriteString(`</tr>`)
 	}
@@ -2249,22 +2236,22 @@ func renderBenchmarkResultsCardFromRuns(title, description, emptyMessage string,
 	return b.String()
 }
 
-func loadBenchmarkHistory(exportDir string) ([]benchmarkHistoryColumn, []benchmarkHistoryRun) {
+func loadBenchmarkHistory(exportDir string) (int, []benchmarkHistoryRun) {
 	baseDir := app.DefaultBenchmarkBaseDir
 	if strings.TrimSpace(exportDir) != "" {
 		baseDir = filepath.Join(exportDir, "bee-benchmark")
 	}
 	paths, err := filepath.Glob(filepath.Join(baseDir, "gpu-benchmark-*", "result.json"))
 	if err != nil || len(paths) == 0 {
-		return nil, nil
+		return -1, nil
 	}
 	sort.Strings(paths)
 	return loadBenchmarkHistoryFromPaths(paths)
 }
 
-func loadBenchmarkHistoryFromPaths(paths []string) ([]benchmarkHistoryColumn, []benchmarkHistoryRun) {
-	columnByKey := make(map[string]benchmarkHistoryColumn)
+func loadBenchmarkHistoryFromPaths(paths []string) (int, []benchmarkHistoryRun) {
 	runs := make([]benchmarkHistoryRun, 0, len(paths))
+	maxGPUIndex := -1
 	for _, path := range paths {
 		raw, err := os.ReadFile(path)
 		if err != nil {
@@ -2277,102 +2264,22 @@ func loadBenchmarkHistoryFromPaths(paths []string) ([]benchmarkHistoryColumn, []
 		run := benchmarkHistoryRun{
 			generatedAt: result.GeneratedAt,
 			displayTime: result.GeneratedAt.Local().Format("2006-01-02 15:04:05"),
-			cells:       make(map[string]benchmarkHistoryCell),
+			gpuScores:   make(map[int]float64),
 		}
-
-		if result.ParallelGPUs {
-			// All GPUs ran simultaneously — one column per server, score = avg composite.
-			gpuModelCount := make(map[string]int)
 		for _, gpu := range result.GPUs {
-				gpuModelCount[strings.TrimSpace(gpu.Name)]++
-			}
-			scoreSum := make(map[string]float64)
-			scoreCnt := make(map[string]int)
-			for _, gpu := range result.GPUs {
-				key := "parallel|" + strings.TrimSpace(result.ServerModel) + "|" + strings.TrimSpace(gpu.Name)
-				scoreSum[key] += gpu.Scores.CompositeScore
-				scoreCnt[key]++
-				count := gpuModelCount[strings.TrimSpace(gpu.Name)]
-				columnByKey[key] = benchmarkHistoryColumn{
-					key:      key,
-					label:    benchmarkHistoryParallelLabel(result.ServerModel, gpu.Name, count),
-					name:     strings.TrimSpace(gpu.Name),
-					index:    -1,
-					parallel: true,
-				}
-			}
-			for key, sum := range scoreSum {
-				run.cells[key] = benchmarkHistoryCell{score: sum / float64(scoreCnt[key]), present: true}
-			}
-		} else {
-			// Each GPU ran independently — one column per GPU index.
-			for _, gpu := range result.GPUs {
-				key := "gpu|" + strings.TrimSpace(result.ServerModel) + "|" + strings.TrimSpace(gpu.Name) + "|" + strconv.Itoa(gpu.Index)
-				columnByKey[key] = benchmarkHistoryColumn{
-					key:      key,
-					label:    benchmarkHistoryPerGPULabel(gpu.Name, gpu.Index),
-					name:     strings.TrimSpace(gpu.Name),
-					index:    gpu.Index,
-					parallel: false,
-				}
-				run.cells[key] = benchmarkHistoryCell{score: gpu.Scores.CompositeScore, present: true}
+			run.gpuScores[gpu.Index] = gpu.Scores.CompositeScore
+			if gpu.Index > maxGPUIndex {
+				maxGPUIndex = gpu.Index
 			}
 		}
 		runs = append(runs, run)
 	}
-
-	columns := make([]benchmarkHistoryColumn, 0, len(columnByKey))
-	for _, col := range columnByKey {
-		columns = append(columns, col)
-	}
-	// Sequential GPU columns first (sorted by GPU index), then parallel server columns.
-	sort.Slice(columns, func(i, j int) bool {
-		if columns[i].parallel != columns[j].parallel {
-			return !columns[i].parallel // sequential first
-		}
-		if columns[i].parallel {
-			li := strings.ToLower(columns[i].label)
-			lj := strings.ToLower(columns[j].label)
-			if li != lj {
-				return li < lj
-			}
-			return columns[i].key < columns[j].key
-		}
-		// Sequential: sort by GPU index, then name.
-		if columns[i].index != columns[j].index {
-			return columns[i].index < columns[j].index
-		}
-		return strings.ToLower(columns[i].name) < strings.ToLower(columns[j].name)
-	})
 	sort.Slice(runs, func(i, j int) bool {
 		return runs[i].generatedAt.After(runs[j].generatedAt)
 	})
-	return columns, runs
+	return maxGPUIndex, runs
 }
 
-// benchmarkHistoryPerGPULabel formats a label for a single-GPU column: "GPU #N — ModelName".
-func benchmarkHistoryPerGPULabel(gpuName string, index int) string {
-	gpuName = strings.TrimSpace(gpuName)
-	if gpuName == "" {
-		gpuName = "Unknown GPU"
-	}
-	return fmt.Sprintf("GPU #%d — %s", index, gpuName)
-}
-
-// benchmarkHistoryParallelLabel formats a label for an all-GPU parallel column:
-// "ServerModel — N× ModelName (All GPUs)" or "N× ModelName (All GPUs)" if no server.
-func benchmarkHistoryParallelLabel(serverModel, gpuName string, count int) string {
-	serverModel = strings.TrimSpace(serverModel)
-	gpuName = strings.TrimSpace(gpuName)
-	if gpuName == "" {
-		gpuName = "Unknown GPU"
-	}
-	gpuPart := fmt.Sprintf("%d× %s (All GPUs)", count, gpuName)
-	if serverModel == "" {
-		return gpuPart
-	}
-	return fmt.Sprintf("%s — %s", serverModel, gpuPart)
-}
 
 // ── Burn ──────────────────────────────────────────────────────────────────────
 

audit/internal/webui/server_test.go

@@ -693,8 +693,8 @@ func TestBenchmarkPageRendersSavedResultsTable(t *testing.T) {
 	for _, needle := range []string{
 		`Benchmark Results`,
 		`Composite score by saved benchmark run and GPU.`,
-		`GPU #0 — NVIDIA H100 PCIe`,
-		`GPU #1 — NVIDIA H100 PCIe`,
+		`GPU 0`,
+		`GPU 1`,
 		`#1`,
 		wantTime,
 		`1176.25`,

audit/internal/webui/tasks_test.go

@@ -422,7 +422,7 @@ func TestWriteTaskReportArtifactsIncludesBenchmarkResultsForTask(t *testing.T) {
 	for _, needle := range []string{
 		`Benchmark Results`,
 		`Composite score for this benchmark task.`,
-		`GPU #0 — NVIDIA H100 PCIe`,
+		`GPU 0`,
 		`1176.25`,
 	} {
 		if !strings.Contains(html, needle) {

iso/builder/VERSIONS

@@ -6,7 +6,7 @@ NCCL_CUDA_VERSION=13.0
 NCCL_SHA256=2e6faafd2c19cffc7738d9283976a3200ea9db9895907f337f0c7e5a25563186
 NCCL_TESTS_VERSION=2.13.10
 NVCC_VERSION=12.8
-CUBLAS_VERSION=13.0.2.14-1
+CUBLAS_VERSION=13.1.1.3-1
 CUDA_USERSPACE_VERSION=13.0.96-1
 DCGM_VERSION=4.5.3-1
 JOHN_JUMBO_COMMIT=67fcf9fe5a

iso/builder/bee-gpu-stress.c

@@ -33,7 +33,6 @@ typedef void *CUstream;
 #define CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR 75
 #define CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR 76
 #define MAX_STRESS_STREAMS 16
-#define MAX_CUBLAS_PROFILES 5
 #define MIN_PROFILE_BUDGET_BYTES ((size_t)4u * 1024u * 1024u)
 #define MIN_STREAM_BUDGET_BYTES ((size_t)64u * 1024u * 1024u)
 
@@ -689,6 +688,8 @@ static const struct profile_desc k_profiles[] = {
 #endif
 };
 
+#define PROFILE_COUNT ((int)(sizeof(k_profiles) / sizeof(k_profiles[0])))
+
 static int load_cublaslt(struct cublaslt_api *api) {
     memset(api, 0, sizeof(*api));
     api->lib = dlopen("libcublasLt.so.13", RTLD_NOW | RTLD_LOCAL);
@@ -1121,9 +1122,10 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
                                int cc_minor,
                                int seconds,
                                int size_mb,
+                               const char *precision_filter,
                                struct stress_report *report) {
     struct cublaslt_api cublas;
-    struct prepared_profile prepared[MAX_STRESS_STREAMS * MAX_CUBLAS_PROFILES];
+    struct prepared_profile prepared[MAX_STRESS_STREAMS * PROFILE_COUNT];
     cublasLtHandle_t handle = NULL;
     CUcontext ctx = NULL;
     CUstream streams[MAX_STRESS_STREAMS] = {0};
@@ -1133,7 +1135,7 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
     int active = 0;
     int mp_count = 0;
     int stream_count = 1;
-    int profile_count = (int)(sizeof(k_profiles) / sizeof(k_profiles[0]));
+    int profile_count = PROFILE_COUNT;
     int prepared_count = 0;
     size_t requested_budget = 0;
     size_t total_budget = 0;
@@ -1158,8 +1160,10 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
         return 0;
     }
 
+    /* Count profiles matching the filter (for deciding what to run). */
     for (size_t i = 0; i < sizeof(k_profiles) / sizeof(k_profiles[0]); i++) {
-        if (k_profiles[i].enabled && cc >= k_profiles[i].min_cc) {
+        if (k_profiles[i].enabled && cc >= k_profiles[i].min_cc &&
+            (precision_filter == NULL || strcmp(k_profiles[i].block_label, precision_filter) == 0)) {
             planned++;
         }
     }
@@ -1170,18 +1174,31 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
         return 0;
     }
 
+    /* Count all profiles active on this GPU regardless of filter.
+     * Used as the budget divisor so matrix sizes stay consistent whether
+     * running all precisions together or a single-precision phase. */
+    int planned_total = 0;
+    for (size_t i = 0; i < sizeof(k_profiles) / sizeof(k_profiles[0]); i++) {
+        if (k_profiles[i].enabled && cc >= k_profiles[i].min_cc) {
+            planned_total++;
+        }
+    }
+    if (planned_total < planned) {
+        planned_total = planned;
+    }
+
     requested_budget = (size_t)size_mb * 1024u * 1024u;
-    if (requested_budget < (size_t)planned * MIN_PROFILE_BUDGET_BYTES) {
-        requested_budget = (size_t)planned * MIN_PROFILE_BUDGET_BYTES;
+    if (requested_budget < (size_t)planned_total * MIN_PROFILE_BUDGET_BYTES) {
+        requested_budget = (size_t)planned_total * MIN_PROFILE_BUDGET_BYTES;
     }
     total_budget = clamp_budget_to_free_memory(cuda, requested_budget);
-    if (total_budget < (size_t)planned * MIN_PROFILE_BUDGET_BYTES) {
-        total_budget = (size_t)planned * MIN_PROFILE_BUDGET_BYTES;
+    if (total_budget < (size_t)planned_total * MIN_PROFILE_BUDGET_BYTES) {
+        total_budget = (size_t)planned_total * MIN_PROFILE_BUDGET_BYTES;
     }
     if (query_multiprocessor_count(cuda, dev, &mp_count) &&
         cuda->cuStreamCreate &&
         cuda->cuStreamDestroy) {
-        stream_count = choose_stream_count(mp_count, planned, total_budget, 1);
+        stream_count = choose_stream_count(mp_count, planned_total, total_budget, 1);
     }
     if (stream_count > 1) {
         int created = 0;
@@ -1194,7 +1211,7 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
         }
     }
     report->stream_count = stream_count;
-    per_profile_budget = total_budget / ((size_t)planned * (size_t)stream_count);
+    per_profile_budget = total_budget / ((size_t)planned_total * (size_t)stream_count);
     if (per_profile_budget < MIN_PROFILE_BUDGET_BYTES) {
         per_profile_budget = MIN_PROFILE_BUDGET_BYTES;
     }
@@ -1218,6 +1235,13 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
                           desc->min_cc);
             continue;
         }
+        if (precision_filter != NULL && strcmp(desc->block_label, precision_filter) != 0) {
+            append_detail(report->details,
+                          sizeof(report->details),
+                          "%s=SKIPPED precision_filter\n",
+                          desc->name);
+            continue;
+        }
         for (int lane = 0; lane < stream_count; lane++) {
             CUstream stream = streams[lane];
             if (prepared_count >= (int)(sizeof(prepared) / sizeof(prepared[0]))) {
@@ -1339,6 +1363,7 @@ int main(int argc, char **argv) {
     int seconds = 5;
     int size_mb = 64;
     int device_index = 0;
+    const char *precision_filter = NULL; /* NULL = all; else block_label to match */
     for (int i = 1; i < argc; i++) {
         if ((strcmp(argv[i], "--seconds") == 0 || strcmp(argv[i], "-t") == 0) && i + 1 < argc) {
             seconds = atoi(argv[++i]);
@@ -1346,8 +1371,12 @@ int main(int argc, char **argv) {
             size_mb = atoi(argv[++i]);
         } else if ((strcmp(argv[i], "--device") == 0 || strcmp(argv[i], "-d") == 0) && i + 1 < argc) {
             device_index = atoi(argv[++i]);
+        } else if (strcmp(argv[i], "--precision") == 0 && i + 1 < argc) {
+            precision_filter = argv[++i];
         } else {
-            fprintf(stderr, "usage: %s [--seconds N] [--size-mb N] [--device N]\n", argv[0]);
+            fprintf(stderr,
+                    "usage: %s [--seconds N] [--size-mb N] [--device N] [--precision fp8|fp16|fp32|fp64|fp4]\n",
+                    argv[0]);
             return 2;
         }
     }
@@ -1407,10 +1436,20 @@ int main(int argc, char **argv) {
     int ok = 0;
 
 #if HAVE_CUBLASLT_HEADERS
-    ok = run_cublaslt_stress(&cuda, dev, name, cc_major, cc_minor, seconds, size_mb, &report);
+    ok = run_cublaslt_stress(&cuda, dev, name, cc_major, cc_minor, seconds, size_mb, precision_filter, &report);
 #endif
     if (!ok) {
-        if (!run_ptx_fallback(&cuda, dev, name, cc_major, cc_minor, seconds, size_mb, &report)) {
+        if (precision_filter != NULL) {
+            fprintf(stderr,
+                    "requested precision path unavailable: precision=%s device=%s cc=%d.%d\n",
+                    precision_filter,
+                    name,
+                    cc_major,
+                    cc_minor);
+            return 1;
+        }
+        int ptx_mb = size_mb;
+        if (!run_ptx_fallback(&cuda, dev, name, cc_major, cc_minor, seconds, ptx_mb, &report)) {
             return 1;
         }
     }

iso/builder/build.sh

@@ -873,9 +873,37 @@ if [ "$BEE_GPU_VENDOR" = "nvidia" ]; then
 
     CUBLAS_CACHE="${DIST_DIR}/cublas-${CUBLAS_VERSION}+cuda${NCCL_CUDA_VERSION}"
 
+    echo "=== bee-gpu-burn FP4 header probe ==="
+    fp4_type_match="$(grep -Rsnm 1 'CUDA_R_4F_E2M1' "${CUBLAS_CACHE}/include" 2>/dev/null || true)"
+    fp4_scale_match="$(grep -Rsnm 1 'CUBLASLT_MATMUL_MATRIX_SCALE_VEC16_UE4M3' "${CUBLAS_CACHE}/include" 2>/dev/null || true)"
+    if [ -n "$fp4_type_match" ]; then
+        echo "fp4_header_symbol=present"
+        echo "$fp4_type_match"
+    else
+        echo "fp4_header_symbol=missing"
+    fi
+    if [ -n "$fp4_scale_match" ]; then
+        echo "fp4_scale_mode_symbol=present"
+        echo "$fp4_scale_match"
+    else
+        echo "fp4_scale_mode_symbol=missing"
+    fi
+
     GPU_STRESS_NEED_BUILD=1
-    if [ -f "$GPU_BURN_WORKER_BIN" ] && [ "${BUILDER_DIR}/bee-gpu-stress.c" -ot "$GPU_BURN_WORKER_BIN" ]; then
+    if [ -f "$GPU_BURN_WORKER_BIN" ]; then
         GPU_STRESS_NEED_BUILD=0
+        for dep in \
+            "${BUILDER_DIR}/bee-gpu-stress.c" \
+            "${BUILDER_DIR}/VERSIONS"; do
+            if [ "$dep" -nt "$GPU_BURN_WORKER_BIN" ]; then
+                GPU_STRESS_NEED_BUILD=1
+                break
+            fi
+        done
+        if [ "$GPU_STRESS_NEED_BUILD" = "0" ] && \
+            find "${CUBLAS_CACHE}/include" "${CUBLAS_CACHE}/lib" -type f -newer "$GPU_BURN_WORKER_BIN" | grep -q .; then
+            GPU_STRESS_NEED_BUILD=1
+        fi
     fi
 
     if [ "$GPU_STRESS_NEED_BUILD" = "1" ]; then
@@ -889,6 +917,12 @@ if [ "$BEE_GPU_VENDOR" = "nvidia" ]; then
     else
         echo "=== bee-gpu-burn worker up to date, skipping build ==="
     fi
+    echo "=== bee-gpu-burn compiled profile probe ==="
+    if grep -aq 'fp4_e2m1' "$GPU_BURN_WORKER_BIN"; then
+        echo "fp4_profile_string=present"
+    else
+        echo "fp4_profile_string=missing"
+    fi
 fi
 
 echo "=== preparing staged overlay (${BUILD_VARIANT}) ==="

iso/overlay/usr/local/bin/bee-gpu-burn

@@ -6,10 +6,11 @@ STAGGER_SECONDS=0
 SIZE_MB=0
 DEVICES=""
 EXCLUDE=""
+PRECISION=""
 WORKER="/usr/local/lib/bee/bee-gpu-burn-worker"
 
 usage() {
-    echo "usage: $0 [--seconds N] [--stagger-seconds N] [--size-mb N] [--devices 0,1] [--exclude 2,3]" >&2
+    echo "usage: $0 [--seconds N] [--stagger-seconds N] [--size-mb N] [--devices 0,1] [--exclude 2,3] [--precision fp8|fp16|fp32|fp64|fp4]" >&2
     exit 2
 }
 
@@ -30,6 +31,7 @@ while [ "$#" -gt 0 ]; do
         --size-mb|-m) [ "$#" -ge 2 ] || usage; SIZE_MB="$2"; shift 2 ;;
         --devices) [ "$#" -ge 2 ] || usage; DEVICES="$2"; shift 2 ;;
         --exclude) [ "$#" -ge 2 ] || usage; EXCLUDE="$2"; shift 2 ;;
+        --precision) [ "$#" -ge 2 ] || usage; PRECISION="$2"; shift 2 ;;
         *) usage ;;
     esac
 done
@@ -88,8 +90,10 @@ for id in $(echo "${FINAL}" | tr ',' ' '); do
     extra_sec=$(( STAGGER_SECONDS * (GPU_COUNT - gpu_pos) ))
     gpu_seconds=$(( SECONDS + extra_sec ))
     echo "starting gpu ${id} size=${gpu_size_mb}MB seconds=${gpu_seconds}"
+    precision_arg=""
+    [ -n "${PRECISION}" ] && precision_arg="--precision ${PRECISION}"
     CUDA_VISIBLE_DEVICES="${id}" \
-        "${WORKER}" --device 0 --seconds "${gpu_seconds}" --size-mb "${gpu_size_mb}" >"${log}" 2>&1 &
+        "${WORKER}" --device 0 --seconds "${gpu_seconds}" --size-mb "${gpu_size_mb}" ${precision_arg} >"${log}" 2>&1 &
     pid=$!
     WORKERS="${WORKERS} ${pid}:${id}:${log}"
     if [ "${STAGGER_SECONDS}" -gt 0 ] && [ "${gpu_pos}" -lt "${GPU_COUNT}" ]; then