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7 Commits
v6.0 ... v6.3

Author SHA1 Message Date
Mikhail Chusavitin
93cfa78e8c Benchmark: parallel GPU mode, resilient inventory query, server model in results
- Add parallel GPU mode (checkbox, off by default): runs all selected GPUs
  simultaneously via a single bee-gpu-burn invocation instead of sequentially;
  per-GPU telemetry, throttle counters, TOPS, and scoring are preserved
- Make queryBenchmarkGPUInfo resilient: falls back to a base field set when
  extended fields (attribute.multiprocessor_count, power.default_limit) cause
  exit status 2, preventing lgc normalization from being silently skipped
- Log explicit "graphics clock lock skipped" note when inventory is unavailable
- Collect server model from DMI (/sys/class/dmi/id/product_name) and store in
  result JSON; benchmark history columns now show "Server Model (N× GPU Model)"
  grouped by server+GPU type rather than individual GPU index

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-07 18:32:15 +03:00
Mikhail Chusavitin
1358485f2b fix logo wallpaper 2026-04-07 10:15:38 +03:00
8fe20ba678 Fix benchmark scoring: PowerSustain uses default power limit
PowerSustainScore now uses DefaultPowerLimitW as reference so a
manually reduced power limit does not inflate the score. Falls back
to enforced limit if default is unavailable.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-06 22:30:59 +03:00
d973231f37 Enhance benchmark: server power via IPMI, efficiency metrics, FP64, power limit check
- Sample server power (IPMI dcmi) during baseline+steady phases in parallel;
  compute delta vs GPU-reported sum; flag ratio < 0.75 as unreliable reporting
- Collect base_graphics_clock_mhz, multiprocessor_count, default_power_limit_w
  from nvidia-smi alongside existing GPU info
- Add tops_per_sm_per_ghz efficiency metric (model-agnostic silicon quality signal)
- Flag when enforced power limit is below default TDP by >5%
- Add fp64 profile to bee-gpu-burn worker (CUDA_R_64F, CUBLAS_COMPUTE_64F, min cc 8.0)
- Improve Executive Summary: overall pass count, FAILED GPU finding
- Throttle counters now shown as % of steady window instead of raw microseconds
- bible-local: clock calibration research, H100/H200 spec, real-world GEMM baselines

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-06 22:26:52 +03:00
f5d175f488 Fix toram: patch live-boot to not use O_DIRECT when replacing loop to tmpfs
losetup --replace --direct-io=on fails with EINVAL when the target file
is on tmpfs (/dev/shm), because tmpfs does not support O_DIRECT.
Strip the --direct-io flag from the replace call and downgrade the
verification failure to a warning so boot continues.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-06 21:06:21 +03:00
fa00667750 Refactor NVIDIA GPU Selection into standalone card on validate page
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-06 21:06:16 +03:00
Mikhail Chusavitin
c7d2816a7f Limit NVIDIA legacy boot hooks to proprietary ISO 2026-04-06 16:33:16 +03:00
15 changed files with 1241 additions and 169 deletions

View File

@@ -27,14 +27,17 @@ type benchmarkProfileSpec struct {
}
type benchmarkGPUInfo struct {
Index int
UUID string
Name string
BusID string
VBIOS string
PowerLimitW float64
MaxGraphicsClockMHz float64
MaxMemoryClockMHz float64
Index int
UUID string
Name string
BusID string
VBIOS string
PowerLimitW float64
DefaultPowerLimitW float64
MaxGraphicsClockMHz float64
MaxMemoryClockMHz float64
BaseGraphicsClockMHz float64
MultiprocessorCount int
}
type benchmarkBurnProfile struct {
@@ -102,7 +105,9 @@ func (s *System) RunNvidiaBenchmark(ctx context.Context, baseDir string, opts Nv
BenchmarkVersion: benchmarkVersion,
GeneratedAt: time.Now().UTC(),
Hostname: hostname,
ServerModel: readServerModel(),
BenchmarkProfile: spec.Name,
ParallelGPUs: opts.ParallelGPUs,
SelectedGPUIndices: append([]int(nil), selected...),
Normalization: BenchmarkNormalization{
Status: "full",
@@ -111,6 +116,11 @@ func (s *System) RunNvidiaBenchmark(ctx context.Context, baseDir string, opts Nv
logFunc(fmt.Sprintf("NVIDIA benchmark profile=%s gpus=%s", spec.Name, joinIndexList(selected)))
// Server power characterization state — populated during per-GPU phases.
var serverIdleW, serverLoadedWSum float64
var serverIdleOK, serverLoadedOK bool
var serverLoadedSamples int
infoByIndex, infoErr := queryBenchmarkGPUInfo(selected)
if infoErr != nil {
result.Warnings = append(result.Warnings, "gpu inventory query failed: "+infoErr.Error())
@@ -135,6 +145,10 @@ func (s *System) RunNvidiaBenchmark(ctx context.Context, baseDir string, opts Nv
}
}()
if opts.ParallelGPUs {
runNvidiaBenchmarkParallel(ctx, verboseLog, runDir, selected, infoByIndex, opts, spec, logFunc, &result, &serverIdleW, &serverLoadedWSum, &serverIdleOK, &serverLoadedOK, &serverLoadedSamples)
} else {
for _, idx := range selected {
gpuResult := BenchmarkGPUResult{
Index: idx,
@@ -146,7 +160,10 @@ func (s *System) RunNvidiaBenchmark(ctx context.Context, baseDir string, opts Nv
gpuResult.BusID = info.BusID
gpuResult.VBIOS = info.VBIOS
gpuResult.PowerLimitW = info.PowerLimitW
gpuResult.MultiprocessorCount = info.MultiprocessorCount
gpuResult.DefaultPowerLimitW = info.DefaultPowerLimitW
gpuResult.MaxGraphicsClockMHz = info.MaxGraphicsClockMHz
gpuResult.BaseGraphicsClockMHz = info.BaseGraphicsClockMHz
gpuResult.MaxMemoryClockMHz = info.MaxMemoryClockMHz
}
if norm := findBenchmarkNormalization(result.Normalization.GPUs, idx); norm != nil {
@@ -161,6 +178,15 @@ func (s *System) RunNvidiaBenchmark(ctx context.Context, baseDir string, opts Nv
gpuResult.Baseline = summarizeBenchmarkTelemetry(baselineRows)
writeBenchmarkMetricsFiles(runDir, fmt.Sprintf("gpu-%d-baseline", idx), baselineRows)
// Sample server idle power once (first GPU only — server state is global).
if !serverIdleOK {
if w, ok := sampleIPMIPowerSeries(ctx, maxInt(spec.BaselineSec, 10)); ok {
serverIdleW = w
serverIdleOK = true
logFunc(fmt.Sprintf("server idle power (IPMI): %.0f W", w))
}
}
warmupCmd := []string{
"bee-gpu-burn",
"--seconds", strconv.Itoa(spec.WarmupSec),
@@ -184,7 +210,50 @@ func (s *System) RunNvidiaBenchmark(ctx context.Context, baseDir string, opts Nv
"--devices", strconv.Itoa(idx),
}
logFunc(fmt.Sprintf("GPU %d: steady compute (%ds)", idx, spec.SteadySec))
// Sample server power via IPMI in parallel with the steady phase.
// We collect readings every 5s and average them.
ipmiStopCh := make(chan struct{})
ipmiResultCh := make(chan float64, 1)
go func() {
defer close(ipmiResultCh)
var samples []float64
ticker := time.NewTicker(5 * time.Second)
defer ticker.Stop()
// First sample after a short warmup delay.
select {
case <-ipmiStopCh:
return
case <-time.After(15 * time.Second):
}
for {
if w, err := queryIPMIServerPowerW(); err == nil {
samples = append(samples, w)
}
select {
case <-ipmiStopCh:
if len(samples) > 0 {
var sum float64
for _, w := range samples {
sum += w
}
ipmiResultCh <- sum / float64(len(samples))
}
return
case <-ticker.C:
}
}
}()
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)
close(ipmiStopCh)
if loadedW, ok := <-ipmiResultCh; ok {
serverLoadedWSum += loadedW
serverLoadedSamples++
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 {
@@ -222,6 +291,8 @@ func (s *System) RunNvidiaBenchmark(ctx context.Context, baseDir string, opts Nv
result.GPUs = append(result.GPUs, finalizeBenchmarkGPUResult(gpuResult))
}
} // end sequential path
if len(selected) > 1 && opts.RunNCCL {
result.Interconnect = runBenchmarkInterconnect(ctx, verboseLog, runDir, selected, spec, logFunc)
if result.Interconnect != nil && result.Interconnect.Supported {
@@ -232,6 +303,17 @@ func (s *System) RunNvidiaBenchmark(ctx context.Context, baseDir string, opts Nv
}
}
// Compute server power characterization from accumulated IPMI samples.
var gpuReportedSumW float64
for _, gpu := range result.GPUs {
gpuReportedSumW += gpu.Steady.AvgPowerW
}
var serverLoadedW float64
if serverLoadedSamples > 0 {
serverLoadedW = serverLoadedWSum / float64(serverLoadedSamples)
}
result.ServerPower = characterizeServerPower(serverIdleW, serverLoadedW, gpuReportedSumW, serverIdleOK && serverLoadedOK)
result.Findings = buildBenchmarkFindings(result)
result.OverallStatus = benchmarkOverallStatus(result)
@@ -288,50 +370,87 @@ func resolveBenchmarkProfile(profile string) benchmarkProfileSpec {
}
}
func queryBenchmarkGPUInfo(gpuIndices []int) (map[int]benchmarkGPUInfo, error) {
args := []string{
"--query-gpu=index,uuid,name,pci.bus_id,vbios_version,power.limit,clocks.max.graphics,clocks.max.memory",
"--format=csv,noheader,nounits",
}
if len(gpuIndices) > 0 {
args = append([]string{"--id=" + joinIndexList(gpuIndices)}, args...)
}
out, err := satExecCommand("nvidia-smi", args...).Output()
if err != nil {
return nil, fmt.Errorf("nvidia-smi gpu info: %w", err)
}
r := csv.NewReader(strings.NewReader(string(out)))
r.TrimLeadingSpace = true
r.FieldsPerRecord = -1
rows, err := r.ReadAll()
if err != nil {
return nil, fmt.Errorf("parse nvidia-smi gpu info: %w", err)
}
infoByIndex := make(map[int]benchmarkGPUInfo, len(rows))
for _, row := range rows {
if len(row) < 8 {
continue
}
idx, err := strconv.Atoi(strings.TrimSpace(row[0]))
if err != nil {
continue
}
infoByIndex[idx] = benchmarkGPUInfo{
Index: idx,
UUID: strings.TrimSpace(row[1]),
Name: strings.TrimSpace(row[2]),
BusID: strings.TrimSpace(row[3]),
VBIOS: strings.TrimSpace(row[4]),
PowerLimitW: parseBenchmarkFloat(row[5]),
MaxGraphicsClockMHz: parseBenchmarkFloat(row[6]),
MaxMemoryClockMHz: parseBenchmarkFloat(row[7]),
}
}
return infoByIndex, nil
// benchmarkGPUInfoQuery describes a nvidia-smi --query-gpu field set to try.
// Fields are tried in order; the first successful query wins. Extended fields
// (attribute.multiprocessor_count, power.default_limit) are not supported on
// all driver versions, so we fall back to the base set if the full query fails.
var benchmarkGPUInfoQueries = []struct {
fields string
extended bool // whether this query includes optional extended fields
}{
{
fields: "index,uuid,name,pci.bus_id,vbios_version,power.limit,clocks.max.graphics,clocks.max.memory,clocks.base.graphics,attribute.multiprocessor_count,power.default_limit",
extended: true,
},
{
fields: "index,uuid,name,pci.bus_id,vbios_version,power.limit,clocks.max.graphics,clocks.max.memory,clocks.base.graphics",
extended: false,
},
}
func queryBenchmarkGPUInfo(gpuIndices []int) (map[int]benchmarkGPUInfo, error) {
var lastErr error
for _, q := range benchmarkGPUInfoQueries {
args := []string{
"--query-gpu=" + q.fields,
"--format=csv,noheader,nounits",
}
if len(gpuIndices) > 0 {
args = append([]string{"--id=" + joinIndexList(gpuIndices)}, args...)
}
out, err := satExecCommand("nvidia-smi", args...).Output()
if err != nil {
lastErr = fmt.Errorf("nvidia-smi gpu info (%s): %w", q.fields[:min(len(q.fields), 40)], err)
continue
}
r := csv.NewReader(strings.NewReader(string(out)))
r.TrimLeadingSpace = true
r.FieldsPerRecord = -1
rows, err := r.ReadAll()
if err != nil {
lastErr = fmt.Errorf("parse nvidia-smi gpu info: %w", err)
continue
}
infoByIndex := make(map[int]benchmarkGPUInfo, len(rows))
for _, row := range rows {
if len(row) < 9 {
continue
}
idx, err := strconv.Atoi(strings.TrimSpace(row[0]))
if err != nil {
continue
}
info := benchmarkGPUInfo{
Index: idx,
UUID: strings.TrimSpace(row[1]),
Name: strings.TrimSpace(row[2]),
BusID: strings.TrimSpace(row[3]),
VBIOS: strings.TrimSpace(row[4]),
PowerLimitW: parseBenchmarkFloat(row[5]),
MaxGraphicsClockMHz: parseBenchmarkFloat(row[6]),
MaxMemoryClockMHz: parseBenchmarkFloat(row[7]),
}
if len(row) >= 9 {
info.BaseGraphicsClockMHz = parseBenchmarkFloat(row[8])
}
if q.extended {
if len(row) >= 10 {
info.MultiprocessorCount = int(parseBenchmarkFloat(row[9]))
}
if len(row) >= 11 {
info.DefaultPowerLimitW = parseBenchmarkFloat(row[10])
}
}
infoByIndex[idx] = info
}
return infoByIndex, nil
}
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"
@@ -370,6 +489,10 @@ func applyBenchmarkNormalization(ctx context.Context, verboseLog string, gpuIndi
_, _ = runSATCommandCtx(context.Background(), verboseLog, fmt.Sprintf("restore-gpu-%d-rgc", idxCopy), []string{"nvidia-smi", "-i", strconv.Itoa(idxCopy), "-rgc"}, nil, nil)
}})
}
} else {
rec.GPUClockLockStatus = "skipped"
rec.Notes = append(rec.Notes, "graphics clock lock skipped: gpu inventory unavailable or MaxGraphicsClockMHz=0")
result.Normalization.Status = "partial"
}
if info, ok := infoByIndex[idx]; ok && info.MaxMemoryClockMHz > 0 {
@@ -551,6 +674,8 @@ func ensureBenchmarkProfile(profiles map[string]*benchmarkBurnProfile, name stri
}
category := "other"
switch {
case strings.HasPrefix(name, "fp64"):
category = "fp64"
case strings.HasPrefix(name, "fp32"):
category = "fp32_tf32"
case strings.HasPrefix(name, "fp16"):
@@ -619,14 +744,23 @@ func scoreBenchmarkGPUResult(gpu BenchmarkGPUResult) BenchmarkScorecard {
score.ComputeScore += precision.TeraOpsPerSec
}
}
if gpu.PowerLimitW > 0 {
score.PowerSustainScore = math.Min(100, (gpu.Steady.AvgPowerW/gpu.PowerLimitW)*100)
// Use default power limit for sustain score so a manually reduced limit
// does not inflate the score. Fall back to enforced limit if default unknown.
referencePowerW := gpu.DefaultPowerLimitW
if referencePowerW <= 0 {
referencePowerW = gpu.PowerLimitW
}
if referencePowerW > 0 {
score.PowerSustainScore = math.Min(100, (gpu.Steady.AvgPowerW/referencePowerW)*100)
}
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))
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)
}
return score
}
@@ -798,10 +932,30 @@ func finalizeBenchmarkGPUResult(gpu BenchmarkGPUResult) BenchmarkGPUResult {
func buildBenchmarkFindings(result NvidiaBenchmarkResult) []string {
var findings []string
passed := 0
for _, gpu := range result.GPUs {
if gpu.Status == "OK" {
passed++
}
}
total := len(result.GPUs)
if total > 0 {
if passed == total {
findings = append(findings, fmt.Sprintf("All %d GPU(s) passed the benchmark.", total))
} else {
findings = append(findings, fmt.Sprintf("%d of %d GPU(s) passed the benchmark.", passed, total))
}
}
if result.Normalization.Status != "full" {
findings = append(findings, "Environment normalization was partial; compare results with caution.")
}
for _, gpu := range result.GPUs {
if gpu.Status == "FAILED" && len(gpu.DegradationReasons) == 0 {
findings = append(findings, fmt.Sprintf("GPU %d failed the benchmark (check verbose.log for details).", gpu.Index))
continue
}
if len(gpu.DegradationReasons) == 0 && gpu.Status == "OK" {
findings = append(findings, fmt.Sprintf("GPU %d held clocks without observable throttle counters during steady state.", gpu.Index))
continue
@@ -825,10 +979,24 @@ func buildBenchmarkFindings(result NvidiaBenchmarkResult) []string {
if gpu.Backend == "driver-ptx" {
findings = append(findings, fmt.Sprintf("GPU %d used driver PTX fallback; tensor score is intentionally degraded.", gpu.Index))
}
if gpu.DefaultPowerLimitW > 0 && gpu.PowerLimitW > 0 && gpu.PowerLimitW < gpu.DefaultPowerLimitW*0.95 {
findings = append(findings, fmt.Sprintf(
"GPU %d power limit %.0f W is below default %.0f W (%.0f%%). Performance may be artificially reduced.",
gpu.Index, gpu.PowerLimitW, gpu.DefaultPowerLimitW, gpu.PowerLimitW/gpu.DefaultPowerLimitW*100,
))
}
}
if result.Interconnect != nil && result.Interconnect.Supported {
findings = append(findings, fmt.Sprintf("Multi-GPU all_reduce max bus bandwidth: %.1f GB/s.", result.Interconnect.MaxBusBWGBps))
}
if sp := result.ServerPower; sp != nil && sp.Available && sp.GPUReportedSumW > 0 {
if sp.ReportingRatio < 0.75 {
findings = append(findings, fmt.Sprintf(
"GPU power reporting may be unreliable: server delta %.0f W vs GPU-reported %.0f W (ratio %.2f). GPU telemetry likely over-reports actual consumption.",
sp.DeltaW, sp.GPUReportedSumW, sp.ReportingRatio,
))
}
}
return dedupeStrings(findings)
}
@@ -1007,3 +1175,319 @@ func maxInt(a, b int) int {
}
return b
}
// 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()
if err != nil {
return 0, fmt.Errorf("ipmitool dcmi power reading: %w", err)
}
for _, line := range strings.Split(string(out), "\n") {
if strings.Contains(line, "Current Power") {
parts := strings.SplitN(line, ":", 2)
if len(parts) == 2 {
val := strings.TrimSpace(strings.TrimSuffix(strings.TrimSpace(parts[1]), "Watts"))
val = strings.TrimSpace(val)
w, err := strconv.ParseFloat(val, 64)
if err == nil && w > 0 {
return w, nil
}
}
}
}
return 0, fmt.Errorf("could not parse ipmitool dcmi power reading output")
}
// sampleIPMIPowerSeries collects IPMI power readings every 2 seconds for
// durationSec seconds. Returns the mean of all successful samples.
// Returns 0, false if IPMI is unavailable.
func sampleIPMIPowerSeries(ctx context.Context, durationSec int) (meanW float64, ok bool) {
if durationSec <= 0 {
return 0, false
}
deadline := time.Now().Add(time.Duration(durationSec) * time.Second)
var samples []float64
for {
if w, err := queryIPMIServerPowerW(); err == nil {
samples = append(samples, w)
}
if time.Now().After(deadline) {
break
}
select {
case <-ctx.Done():
break
case <-time.After(2 * time.Second):
}
}
if len(samples) == 0 {
return 0, false
}
var sum float64
for _, w := range samples {
sum += w
}
return sum / float64(len(samples)), true
}
// characterizeServerPower computes BenchmarkServerPower from idle and loaded
// IPMI samples plus the GPU-reported average power during steady state.
func characterizeServerPower(idleW, loadedW, gpuReportedSumW float64, ipmiAvailable bool) *BenchmarkServerPower {
sp := &BenchmarkServerPower{Available: ipmiAvailable}
if !ipmiAvailable {
sp.Notes = append(sp.Notes, "IPMI power reading unavailable; server-side power characterization skipped")
return sp
}
sp.IdleW = idleW
sp.LoadedW = loadedW
sp.DeltaW = loadedW - idleW
sp.GPUReportedSumW = gpuReportedSumW
if gpuReportedSumW > 0 && sp.DeltaW > 0 {
sp.ReportingRatio = sp.DeltaW / gpuReportedSumW
}
return sp
}
// readServerModel returns the DMI system product name (e.g. "SuperMicro SYS-421GE-TNRT").
// Returns empty string if unavailable (non-Linux or missing DMI entry).
func readServerModel() string {
data, err := os.ReadFile("/sys/class/dmi/id/product_name")
if err != nil {
return ""
}
return strings.TrimSpace(string(data))
}
// filterRowsByGPU returns only the metric rows for a specific GPU index.
func filterRowsByGPU(rows []GPUMetricRow, gpuIndex int) []GPUMetricRow {
var out []GPUMetricRow
for _, r := range rows {
if r.GPUIndex == gpuIndex {
out = append(out, r)
}
}
return out
}
// parseBenchmarkBurnLogByGPU splits a multi-GPU bee-gpu-burn output by [gpu N] prefix
// and returns a per-GPU parse result map.
func parseBenchmarkBurnLogByGPU(raw string) map[int]benchmarkBurnParseResult {
gpuLines := make(map[int][]string)
for _, line := range strings.Split(strings.ReplaceAll(raw, "\r\n", "\n"), "\n") {
line = strings.TrimSpace(line)
if !strings.HasPrefix(line, "[gpu ") {
continue
}
end := strings.Index(line, "] ")
if end < 0 {
continue
}
gpuIdx, err := strconv.Atoi(strings.TrimSpace(line[5:end]))
if err != nil {
continue
}
gpuLines[gpuIdx] = append(gpuLines[gpuIdx], line[end+2:])
}
results := make(map[int]benchmarkBurnParseResult, len(gpuLines))
for gpuIdx, lines := range gpuLines {
// Lines are already stripped of the [gpu N] prefix; parseBenchmarkBurnLog
// calls stripBenchmarkPrefix which is a no-op on already-stripped lines.
results[gpuIdx] = parseBenchmarkBurnLog(strings.Join(lines, "\n"))
}
return results
}
// runNvidiaBenchmarkParallel runs warmup and steady compute on all selected GPUs
// simultaneously using a single bee-gpu-burn invocation per phase.
func runNvidiaBenchmarkParallel(
ctx context.Context,
verboseLog, runDir string,
selected []int,
infoByIndex map[int]benchmarkGPUInfo,
opts NvidiaBenchmarkOptions,
spec benchmarkProfileSpec,
logFunc func(string),
result *NvidiaBenchmarkResult,
serverIdleW *float64, serverLoadedWSum *float64,
serverIdleOK *bool, serverLoadedOK *bool, serverLoadedSamples *int,
) {
allDevices := joinIndexList(selected)
// Build per-GPU result stubs.
gpuResults := make(map[int]*BenchmarkGPUResult, len(selected))
for _, idx := range selected {
r := &BenchmarkGPUResult{Index: idx, Status: "FAILED"}
if info, ok := infoByIndex[idx]; ok {
r.UUID = info.UUID
r.Name = info.Name
r.BusID = info.BusID
r.VBIOS = info.VBIOS
r.PowerLimitW = info.PowerLimitW
r.MultiprocessorCount = info.MultiprocessorCount
r.DefaultPowerLimitW = info.DefaultPowerLimitW
r.MaxGraphicsClockMHz = info.MaxGraphicsClockMHz
r.BaseGraphicsClockMHz = info.BaseGraphicsClockMHz
r.MaxMemoryClockMHz = info.MaxMemoryClockMHz
}
if norm := findBenchmarkNormalization(result.Normalization.GPUs, idx); norm != nil {
r.LockedGraphicsClockMHz = norm.GPUClockLockMHz
r.LockedMemoryClockMHz = norm.MemoryClockLockMHz
}
gpuResults[idx] = r
}
// Baseline: sample all GPUs together.
baselineRows, err := collectBenchmarkSamples(ctx, spec.BaselineSec, selected)
if err != nil && err != context.Canceled {
for _, idx := range selected {
gpuResults[idx].Notes = append(gpuResults[idx].Notes, "baseline sampling failed: "+err.Error())
}
}
for _, idx := range selected {
perGPU := filterRowsByGPU(baselineRows, idx)
gpuResults[idx].Baseline = summarizeBenchmarkTelemetry(perGPU)
writeBenchmarkMetricsFiles(runDir, fmt.Sprintf("gpu-%d-baseline", idx), perGPU)
}
// Sample server idle power once.
if !*serverIdleOK {
if w, ok := sampleIPMIPowerSeries(ctx, maxInt(spec.BaselineSec, 10)); ok {
*serverIdleW = w
*serverIdleOK = true
logFunc(fmt.Sprintf("server idle power (IPMI): %.0f W", w))
}
}
// Warmup: all GPUs simultaneously.
warmupCmd := []string{
"bee-gpu-burn",
"--seconds", strconv.Itoa(spec.WarmupSec),
"--size-mb", strconv.Itoa(opts.SizeMB),
"--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))
}
if warmupErr != nil {
for _, idx := range selected {
gpuResults[idx].Notes = append(gpuResults[idx].Notes, "parallel warmup failed: "+warmupErr.Error())
}
}
// Snapshot throttle counters before steady.
beforeThrottle := make(map[int]BenchmarkThrottleCounters, len(selected))
for _, idx := range selected {
beforeThrottle[idx], _ = queryThrottleCounters(idx)
}
// Steady: all GPUs simultaneously.
steadyCmd := []string{
"bee-gpu-burn",
"--seconds", strconv.Itoa(spec.SteadySec),
"--size-mb", strconv.Itoa(opts.SizeMB),
"--devices", allDevices,
}
logFunc(fmt.Sprintf("GPUs %s: parallel steady compute (%ds)", allDevices, spec.SteadySec))
// Sample server power via IPMI in parallel with steady phase.
ipmiStopCh := make(chan struct{})
ipmiResultCh := make(chan float64, 1)
go func() {
defer close(ipmiResultCh)
var samples []float64
ticker := time.NewTicker(5 * time.Second)
defer ticker.Stop()
select {
case <-ipmiStopCh:
return
case <-time.After(15 * time.Second):
}
for {
if w, err := queryIPMIServerPowerW(); err == nil {
samples = append(samples, w)
}
select {
case <-ipmiStopCh:
if len(samples) > 0 {
var sum float64
for _, w := range samples {
sum += w
}
ipmiResultCh <- sum / float64(len(samples))
}
return
case <-ticker.C:
}
}
}()
steadyOut, steadyRows, steadyErr := runBenchmarkCommandWithMetrics(ctx, verboseLog, "gpu-all-steady.log", steadyCmd, nil, selected, runDir, "gpu-all-steady", logFunc)
close(ipmiStopCh)
if loadedW, ok := <-ipmiResultCh; ok {
*serverLoadedWSum += loadedW
(*serverLoadedSamples)++
*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)
}
parseResults := parseBenchmarkBurnLogByGPU(string(steadyOut))
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 pr, ok := parseResults[idx]; ok {
gpuResults[idx].ComputeCapability = pr.ComputeCapability
gpuResults[idx].Backend = pr.Backend
gpuResults[idx].PrecisionResults = pr.Profiles
if pr.Fallback {
gpuResults[idx].Notes = append(gpuResults[idx].Notes, "benchmark used driver PTX fallback; tensor throughput score is not comparable")
}
}
if steadyErr != nil {
gpuResults[idx].Notes = append(gpuResults[idx].Notes, "parallel steady compute failed: "+steadyErr.Error())
}
}
// Cooldown: all GPUs together.
cooldownRows, err := collectBenchmarkSamples(ctx, spec.CooldownSec, selected)
if err != nil && err != context.Canceled {
for _, idx := range selected {
gpuResults[idx].Notes = append(gpuResults[idx].Notes, "cooldown sampling failed: "+err.Error())
}
}
for _, idx := range selected {
perGPU := filterRowsByGPU(cooldownRows, idx)
gpuResults[idx].Cooldown = summarizeBenchmarkTelemetry(perGPU)
writeBenchmarkMetricsFiles(runDir, fmt.Sprintf("gpu-%d-cooldown", idx), perGPU)
}
// Score and finalize each GPU.
for _, idx := range selected {
r := gpuResults[idx]
r.Scores = scoreBenchmarkGPUResult(*r)
r.DegradationReasons = detectBenchmarkDegradationReasons(*r, result.Normalization.Status)
pr := parseResults[idx]
switch {
case steadyErr != nil:
r.Status = classifySATErrorStatus(steadyOut, steadyErr)
case pr.Fallback:
r.Status = "PARTIAL"
default:
r.Status = "OK"
}
result.GPUs = append(result.GPUs, finalizeBenchmarkGPUResult(*r))
}
}

View File

@@ -56,6 +56,9 @@ func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult, charts []benc
fmt.Fprintf(&b, " Status: %s\n", gpu.Status)
fmt.Fprintf(&b, " Composite score: %.2f\n", gpu.Scores.CompositeScore)
fmt.Fprintf(&b, " Compute score: %.2f\n", gpu.Scores.ComputeScore)
if gpu.Scores.TOPSPerSMPerGHz > 0 {
fmt.Fprintf(&b, " Compute efficiency: %.3f TOPS/SM/GHz\n", gpu.Scores.TOPSPerSMPerGHz)
}
fmt.Fprintf(&b, " Power sustain: %.1f\n", gpu.Scores.PowerSustainScore)
fmt.Fprintf(&b, " Thermal sustain: %.1f\n", gpu.Scores.ThermalSustainScore)
fmt.Fprintf(&b, " Stability: %.1f\n", gpu.Scores.StabilityScore)
@@ -77,13 +80,7 @@ func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult, charts []benc
}
}
}
fmt.Fprintf(&b, " Throttle counters (us): sw_power=%d sw_thermal=%d sync_boost=%d hw_thermal=%d hw_power_brake=%d\n",
gpu.Throttle.SWPowerCapUS,
gpu.Throttle.SWThermalSlowdownUS,
gpu.Throttle.SyncBoostUS,
gpu.Throttle.HWThermalSlowdownUS,
gpu.Throttle.HWPowerBrakeSlowdownUS,
)
fmt.Fprintf(&b, " Throttle: %s\n", formatThrottleLine(gpu.Throttle, gpu.Steady.DurationSec))
if len(gpu.Notes) > 0 {
fmt.Fprintf(&b, " Notes:\n")
for _, note := range gpu.Notes {
@@ -121,6 +118,26 @@ func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult, charts []benc
}
}
if sp := result.ServerPower; sp != nil {
fmt.Fprintf(&b, "Server Power (IPMI)\n")
fmt.Fprintf(&b, "-------------------\n")
if !sp.Available {
fmt.Fprintf(&b, "Unavailable\n")
} else {
fmt.Fprintf(&b, " Server idle: %.0f W\n", sp.IdleW)
fmt.Fprintf(&b, " Server under load: %.0f W\n", sp.LoadedW)
fmt.Fprintf(&b, " Server delta: %.0f W\n", sp.DeltaW)
fmt.Fprintf(&b, " GPU reported (sum): %.0f W\n", sp.GPUReportedSumW)
if sp.ReportingRatio > 0 {
fmt.Fprintf(&b, " Reporting ratio: %.2f (1.0 = accurate, <0.75 = GPU over-reports)\n", sp.ReportingRatio)
}
}
for _, note := range sp.Notes {
fmt.Fprintf(&b, " Note: %s\n", note)
}
b.WriteString("\n")
}
fmt.Fprintf(&b, "Methodology\n")
fmt.Fprintf(&b, "-----------\n")
fmt.Fprintf(&b, "- Profile %s uses standardized baseline, warmup, steady-state, interconnect, and cooldown phases.\n", result.BenchmarkProfile)
@@ -175,6 +192,42 @@ 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.
func formatThrottleLine(t BenchmarkThrottleCounters, steadyDurationSec float64) string {
type counter struct {
label string
us uint64
}
counters := []counter{
{"sw_power", t.SWPowerCapUS},
{"sw_thermal", t.SWThermalSlowdownUS},
{"sync_boost", t.SyncBoostUS},
{"hw_thermal", t.HWThermalSlowdownUS},
{"hw_power_brake", t.HWPowerBrakeSlowdownUS},
}
var parts []string
for _, c := range counters {
if c.us == 0 {
continue
}
sec := float64(c.us) / 1e6
if steadyDurationSec > 0 {
pct := sec / steadyDurationSec * 100
parts = append(parts, fmt.Sprintf("%s=%.1f%% (%.0fs)", c.label, pct, sec))
} else if sec < 1 {
parts = append(parts, fmt.Sprintf("%s=%.0fms", c.label, sec*1000))
} else {
parts = append(parts, fmt.Sprintf("%s=%.1fs", c.label, sec))
}
}
if len(parts) == 0 {
return "none"
}
return strings.Join(parts, " ")
}
func renderBenchmarkSummary(result NvidiaBenchmarkResult) string {
var b strings.Builder
fmt.Fprintf(&b, "run_at_utc=%s\n", result.GeneratedAt.Format(time.RFC3339))

View File

@@ -14,13 +14,17 @@ type NvidiaBenchmarkOptions struct {
GPUIndices []int
ExcludeGPUIndices []int
RunNCCL bool
ParallelGPUs bool // run all selected GPUs simultaneously instead of sequentially
}
type NvidiaBenchmarkResult struct {
BenchmarkVersion string `json:"benchmark_version"`
GeneratedAt time.Time `json:"generated_at"`
Hostname string `json:"hostname,omitempty"`
ServerModel string `json:"server_model,omitempty"`
BenchmarkProfile string `json:"benchmark_profile"`
ParallelGPUs bool `json:"parallel_gpus,omitempty"`
OverallStatus string `json:"overall_status"`
SelectedGPUIndices []int `json:"selected_gpu_indices"`
Findings []string `json:"findings,omitempty"`
@@ -28,6 +32,7 @@ type NvidiaBenchmarkResult struct {
Normalization BenchmarkNormalization `json:"normalization"`
GPUs []BenchmarkGPUResult `json:"gpus"`
Interconnect *BenchmarkInterconnectResult `json:"interconnect,omitempty"`
ServerPower *BenchmarkServerPower `json:"server_power,omitempty"`
}
type BenchmarkNormalization struct {
@@ -56,7 +61,10 @@ type BenchmarkGPUResult struct {
Backend string `json:"backend,omitempty"`
Status string `json:"status"`
PowerLimitW float64 `json:"power_limit_w,omitempty"`
MultiprocessorCount int `json:"multiprocessor_count,omitempty"`
DefaultPowerLimitW float64 `json:"default_power_limit_w,omitempty"`
MaxGraphicsClockMHz float64 `json:"max_graphics_clock_mhz,omitempty"`
BaseGraphicsClockMHz float64 `json:"base_graphics_clock_mhz,omitempty"`
MaxMemoryClockMHz float64 `json:"max_memory_clock_mhz,omitempty"`
LockedGraphicsClockMHz float64 `json:"locked_graphics_clock_mhz,omitempty"`
LockedMemoryClockMHz float64 `json:"locked_memory_clock_mhz,omitempty"`
@@ -117,6 +125,24 @@ type BenchmarkScorecard struct {
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"`
}
// BenchmarkServerPower captures server-side power via IPMI alongside GPU-reported
// power. The reporting_ratio (delta / gpu_reported_sum) near 1.0 means GPU power
// telemetry is accurate; a ratio well below 1.0 (e.g. 0.5) means the GPU is
// over-reporting its power consumption.
type BenchmarkServerPower struct {
Available bool `json:"available"`
IdleW float64 `json:"idle_w,omitempty"`
LoadedW float64 `json:"loaded_w,omitempty"`
DeltaW float64 `json:"delta_w,omitempty"`
GPUReportedSumW float64 `json:"gpu_reported_sum_w,omitempty"`
ReportingRatio float64 `json:"reporting_ratio,omitempty"`
Notes []string `json:"notes,omitempty"`
}
type BenchmarkInterconnectResult struct {

View File

@@ -470,6 +470,7 @@ func (h *handler) handleAPIBenchmarkNvidiaRun(w http.ResponseWriter, r *http.Req
GPUIndices []int `json:"gpu_indices"`
ExcludeGPUIndices []int `json:"exclude_gpu_indices"`
RunNCCL *bool `json:"run_nccl"`
ParallelGPUs *bool `json:"parallel_gpus"`
DisplayName string `json:"display_name"`
}
if r.Body != nil {
@@ -483,6 +484,10 @@ func (h *handler) handleAPIBenchmarkNvidiaRun(w http.ResponseWriter, r *http.Req
if body.RunNCCL != nil {
runNCCL = *body.RunNCCL
}
parallelGPUs := false
if body.ParallelGPUs != nil {
parallelGPUs = *body.ParallelGPUs
}
name := taskDisplayName("nvidia-benchmark", "", "")
if strings.TrimSpace(body.DisplayName) != "" {
name = body.DisplayName
@@ -493,6 +498,7 @@ func (h *handler) handleAPIBenchmarkNvidiaRun(w http.ResponseWriter, r *http.Req
SizeMB: body.SizeMB,
BenchmarkProfile: body.Profile,
RunNCCL: runNCCL,
ParallelGPUs: parallelGPUs,
DisplayName: body.DisplayName,
}, name, h.opts.App, "benchmark-nvidia")
if err != nil {

View File

@@ -1070,14 +1070,24 @@ func renderValidate(opts HandlerOptions) string {
)) +
`</div>
<div style="height:1px;background:var(--border);margin:16px 0"></div>
<div class="card" style="margin-bottom:16px">
<div class="card-head">NVIDIA GPU Selection</div>
<div class="card-body">
<p style="font-size:12px;color:var(--muted);margin:0 0 8px">` + inv.NVIDIA + `</p>
<p style="font-size:12px;color:var(--muted);margin:0 0 10px">All NVIDIA validate tasks use only the GPUs selected here. The same selection is used by Validate one by one.</p>
<div style="display:flex;gap:8px;flex-wrap:wrap;margin-bottom:8px">
<button class="btn btn-sm btn-secondary" type="button" onclick="satSelectAllGPUs()">Select All</button>
<button class="btn btn-sm btn-secondary" type="button" onclick="satSelectNoGPUs()">Clear</button>
</div>
<div id="sat-gpu-list" style="border:1px solid var(--border);border-radius:4px;padding:12px;min-height:88px">
<p style="color:var(--muted);font-size:13px">Loading NVIDIA GPUs...</p>
</div>
<p id="sat-gpu-selection-note" style="font-size:12px;color:var(--muted);margin:10px 0 0">Select at least one NVIDIA GPU to enable NVIDIA validate tasks.</p>
</div>
</div>
<div class="grid3">
` + renderSATCard("nvidia-selection", "NVIDIA GPU Selection", "", "", renderValidateCardBody(
inv.NVIDIA,
`Select which NVIDIA GPUs to include in Validate. The same selection is used by both NVIDIA GPU cards below and by Validate one by one.`,
`<code>nvidia-smi --query-gpu=index,name,memory.total</code>`,
`<div id="sat-gpu-list"><p style="color:var(--muted);font-size:13px">Loading NVIDIA GPUs…</p></div><div style="display:flex;gap:8px;flex-wrap:wrap;margin-top:8px"><button type="button" class="btn btn-sm btn-secondary" onclick="satSelectAllGPUs()">Select all</button><button type="button" class="btn btn-sm btn-secondary" onclick="satSelectNoGPUs()">Clear</button></div><div id="sat-gpu-selection-note" style="font-size:12px;color:var(--muted);margin-top:8px"></div>`,
)) +
renderSATCard("nvidia", "NVIDIA GPU", "runNvidiaValidateSet('nvidia')", "", renderValidateCardBody(
` + renderSATCard("nvidia", "NVIDIA GPU", "runNvidiaValidateSet('nvidia')", "", renderValidateCardBody(
inv.NVIDIA,
`Runs NVIDIA diagnostics and board inventory checks.`,
`<code>nvidia-smi</code>, <code>dmidecode</code>, <code>dcgmi diag</code>`,
@@ -1615,6 +1625,10 @@ func renderBenchmark(opts HandlerOptions) string {
<p style="color:var(--muted);font-size:13px">Loading NVIDIA GPUs...</p>
</div>
</div>
<label class="benchmark-cb-row">
<input type="checkbox" id="benchmark-parallel-gpus">
<span>Run all selected GPUs simultaneously (parallel mode)</span>
</label>
<label class="benchmark-cb-row">
<input type="checkbox" id="benchmark-run-nccl" checked>
<span>Run multi-GPU interconnect step (NCCL) only on the selected GPUs</span>
@@ -1740,10 +1754,12 @@ function runNvidiaBenchmark() {
return;
}
if (benchmarkES) { benchmarkES.close(); benchmarkES = null; }
const parallelGPUs = !!document.getElementById('benchmark-parallel-gpus').checked;
const body = {
profile: document.getElementById('benchmark-profile').value || 'standard',
gpu_indices: selected,
run_nccl: !!document.getElementById('benchmark-run-nccl').checked,
parallel_gpus: parallelGPUs,
display_name: 'NVIDIA Benchmark'
};
document.getElementById('benchmark-output').style.display = 'block';
@@ -1877,19 +1893,31 @@ func loadBenchmarkHistoryFromPaths(paths []string) ([]benchmarkHistoryColumn, []
displayTime: result.GeneratedAt.Local().Format("2006-01-02 15:04:05"),
cells: make(map[string]benchmarkHistoryCell),
}
// Count how many GPUs of each model appear in this run (for the label).
gpuModelCount := make(map[string]int)
for _, gpu := range result.GPUs {
key := benchmarkHistoryColumnKey(gpu.Name, gpu.Index)
gpuModelCount[strings.TrimSpace(gpu.Name)]++
}
// Track best composite score per column key within this run.
runBest := make(map[string]float64)
for _, gpu := range result.GPUs {
key := benchmarkHistoryColumnKey(result.ServerModel, gpu.Name)
count := gpuModelCount[strings.TrimSpace(gpu.Name)]
columnByKey[key] = benchmarkHistoryColumn{
key: key,
label: benchmarkHistoryColumnLabel(gpu.Name, gpu.Index),
label: benchmarkHistoryColumnLabel(result.ServerModel, gpu.Name, count),
name: strings.TrimSpace(gpu.Name),
index: gpu.Index,
}
run.cells[key] = benchmarkHistoryCell{
score: gpu.Scores.CompositeScore,
present: true,
if gpu.Scores.CompositeScore > runBest[key] {
runBest[key] = gpu.Scores.CompositeScore
}
}
for key, score := range runBest {
run.cells[key] = benchmarkHistoryCell{score: score, present: true}
}
runs = append(runs, run)
}
@@ -1898,13 +1926,10 @@ func loadBenchmarkHistoryFromPaths(paths []string) ([]benchmarkHistoryColumn, []
columns = append(columns, col)
}
sort.Slice(columns, func(i, j int) bool {
leftName := strings.ToLower(strings.TrimSpace(columns[i].name))
rightName := strings.ToLower(strings.TrimSpace(columns[j].name))
if leftName != rightName {
return leftName < rightName
}
if columns[i].index != columns[j].index {
return columns[i].index < columns[j].index
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
})
@@ -1914,16 +1939,25 @@ func loadBenchmarkHistoryFromPaths(paths []string) ([]benchmarkHistoryColumn, []
return columns, runs
}
func benchmarkHistoryColumnKey(name string, index int) string {
return strings.TrimSpace(name) + "|" + strconv.Itoa(index)
// benchmarkHistoryColumnKey groups results by server model + GPU model so that
// runs on the same hardware produce one column regardless of individual GPU index.
func benchmarkHistoryColumnKey(serverModel, gpuName string) string {
return strings.TrimSpace(serverModel) + "|" + strings.TrimSpace(gpuName)
}
func benchmarkHistoryColumnLabel(name string, index int) string {
name = strings.TrimSpace(name)
if name == "" {
return fmt.Sprintf("GPU %d", index)
// benchmarkHistoryColumnLabel formats the column header as
// "Server Model (N× GPU Model)" or "GPU Model" when server info is missing.
func benchmarkHistoryColumnLabel(serverModel, gpuName string, count int) string {
serverModel = strings.TrimSpace(serverModel)
gpuName = strings.TrimSpace(gpuName)
if gpuName == "" {
gpuName = "Unknown GPU"
}
return fmt.Sprintf("%s / GPU %d", name, index)
gpuPart := fmt.Sprintf("%d× %s", count, gpuName)
if serverModel == "" {
return gpuPart
}
return fmt.Sprintf("%s (%s)", serverModel, gpuPart)
}
// ── Burn ──────────────────────────────────────────────────────────────────────

View File

@@ -711,6 +711,8 @@ func TestValidatePageRendersNvidiaTargetedStressCard(t *testing.T) {
`controlled NVIDIA DCGM load`,
`<code>dcgmi diag targeted_stress</code>`,
`NVIDIA GPU Selection`,
`All NVIDIA validate tasks use only the GPUs selected here.`,
`Select All`,
`id="sat-gpu-list"`,
} {
if !strings.Contains(body, needle) {

View File

@@ -123,6 +123,7 @@ type taskParams struct {
BurnProfile string `json:"burn_profile,omitempty"`
BenchmarkProfile string `json:"benchmark_profile,omitempty"`
RunNCCL bool `json:"run_nccl,omitempty"`
ParallelGPUs bool `json:"parallel_gpus,omitempty"`
DisplayName string `json:"display_name,omitempty"`
Device string `json:"device,omitempty"` // for install
PlatformComponents []string `json:"platform_components,omitempty"`
@@ -585,6 +586,7 @@ func (q *taskQueue) runTask(t *Task, j *jobState, ctx context.Context) {
GPUIndices: t.params.GPUIndices,
ExcludeGPUIndices: t.params.ExcludeGPUIndices,
RunNCCL: t.params.RunNCCL,
ParallelGPUs: t.params.ParallelGPUs,
}, j.append)
case "nvidia-compute":
if a == nil {

2
bible

Submodule bible updated: 1d89a4918e...688b87e98d

View File

@@ -0,0 +1,248 @@
# Benchmark clock calibration research
## Status
In progress. Baseline data from production servers pending.
## Background
The benchmark locks GPU clocks to `MaxGraphicsClockMHz` (boost) via `nvidia-smi -lgc`
before the steady-state phase. The metric `low_sm_clock_vs_target` fires when
`avg_steady_clock < locked_target * 0.90`.
Problem: boost clock is the theoretical maximum under ideal cooling. In practice,
even a healthy GPU in a non-ideal server will sustain clocks well below boost.
The 90% threshold has no empirical basis.
## Key observations (2026-04-06)
### H100 PCIe — new card, server not designed for it
- avg clock 1384 MHz, P95 1560 MHz (unstable, proba boost 1755 MHz)
- Thermal sustain: 0.0 (sw_thermal covers entire steady window)
- Stability: 70.0 — clocks erratic, no equilibrium found
- Degradation: power_capped, thermal_limited, low_sm_clock_vs_target, variance_too_high
### H200 NVL — new card, server not designed for it
- avg clock = P95 = 1635 MHz (perfectly stable)
- Thermal sustain: 0.0 (sw_thermal + sw_power cover entire steady window)
- Stability: 92.0 — found stable thermal equilibrium at 1635 MHz
- Degradation: power_capped, thermal_limited
- Compute: 989 TOPS — card is computing correctly for its frequency
### Key insight
The meaningful distinction is not *whether* the card throttles but *how stably*
it throttles. H200 found a thermal equilibrium (avg == P95, Stability 92),
H100 did not (avg << P95, Stability 70). Both are new cards; the H100's
instability may reflect a more severe thermal mismatch or a card issue.
`sw_power ≈ sw_thermal` pattern = server cooling constraint, card likely OK.
`hw_thermal >> sw_thermal` pattern = card itself overheating, investigate.
## Hypothesis for baseline
After testing on servers designed for their GPUs (proper cooling):
- Healthy GPU under sustained load will run at a stable fraction of boost
- Expected: avg_steady ≈ 8095% of boost depending on model and TDP class
- Base clock (`clocks.base.gr`) may be a better reference than boost:
a healthy card under real workload should comfortably exceed base clock
## Baseline: H100 PCIe HBM2e — designed server (2026-04-06, 10 samples)
Source: external stress test tool, ~90s runs, designed server, adequate power.
### Healthy fingerprint
- **Power**: hits cap ~340360W immediately, stays flat throughout — HEALTHY
- **Clock**: starts ~1750 MHz, oscillates and declines to ~15401600 MHz by 90s
- Avg steady (visual): **~15801620 MHz**
- vs boost 1755 MHz: **~9192%**
- Oscillation is NORMAL — this is the boost algorithm balancing under power cap
- Stable power + oscillating clocks = healthy power-cap behavior
- **Temperature**: linear rise ~38°C → 7580°C over 90s (no runaway)
- **Consistency**: all 10 samples within ±20 MHz — very repeatable
### Characteristic patten
Flat power line + oscillating/declining clock line = GPU correctly managed by
power cap algorithm. Do NOT flag this as instability.
### Clock CV implication
The healthy oscillation WILL produce moderate ClockCVPct (~510%).
The current `variance_too_high` threshold (StabilityScore < 85) may fire on
healthy HBM2e PCIe cards. Needs recalibration.
---
## Baseline: H100 HBM3 OEM SXM Custom (restored) — 2 confirmed samples
Source: pytorch_training_loop stress test, 120s (90s stress + 30s cooldown).
Confirmed GPU: NVIDIA H100 80GB HBM3, GH100 rev a1.
### GPU clock reference (from nvidia-smi, idle):
- base_clock_mhz: **1095**
- boost_clock_mhz: **1755** (nvidia-smi `clocks.max.graphics` at idle)
- achieved_max_clock_mhz: **1980** (actual burst max observed by tool)
- Our benchmark locks to `clocks.max.graphics` = likely 1980 MHz for this chip
### Observed under 700W sustained load (both samples nearly identical):
- Power: ~700W flat — SXM slot, adequate power confirmed
- Clock steady range: **~13801480 MHz**, avg **~14201460 MHz**
- vs 1980 MHz (lock target): **7274%** — severely below
- vs 1755 MHz (nvidia-smi boost): **8183%**
- vs 1095 MHz (base): 130% — above base but far below expected for SXM
- Clock/Watt: ~2.1 MHz/W vs HBM2e ~4.6 MHz/W — 2× worse efficiency
- Temperature: 38°C → 7980°C (same rate as HBM2e)
- Oscillation: present, similar character to HBM2e but at much lower frequency
### Diagnosis
These restored cards are degraded. A healthy H100 SXM in a designed server
(DGX H100, HGX H100) should sustain ~18001900 MHz at 700W (~9196% of 1980).
The 7274% result is a clear signal of silicon or VRM degradation from the
refurbishment process.
### Clock pattern note
Images 8/9 (previously marked as "HBM3 restored") are now confirmed identical
to images 19/20. Both sample sets show same degraded pattern — same batch.
---
## Baseline matrix (filled where data available)
| GPU model | Config | Avg clock steady | vs boost | Clock/Watt | Notes |
|---|---|---|---|---|---|
| H100 PCIe HBM2e | designed server | 15801620 MHz | 9192% | ~4.6 MHz/W | 10 samples, healthy |
| H100 SXM HBM3 restored | 700W full | 14201460 MHz | 7274% of 1980 | ~2.1 MHz/W | 4 samples confirmed, degraded |
| H100 SXM HBM3 healthy | designed | ~18001900 MHz est. | ~9196% est. | ~2.7 MHz/W est. | need real baseline |
| H200 NVL | designed | TBD | TBD | TBD | need baseline |
---
## H100 official spec (from NVIDIA datasheet)
Source: NVIDIA H100 Tensor Core GPU Datasheet (image 23, 2026-04-06).
All TOPS marked * are with structural sparsity enabled. Divide by 2 for dense.
| Model | FP16 Tensor (dense) | TF32 (dense) | FP8 (dense) | TDP | Memory |
|---|---|---|---|---|---|
| H100 80GB PCIe | 756 TFLOPS | 378 TFLOPS | 1,513 TFLOPS | 350W | HBM2e |
| H100 NVL 94GB PCIe | 990 TFLOPS | 495 TFLOPS | 1,980 TFLOPS | 400W | HBM3 |
| H100 80GB SXM (BQQV) | 989 TFLOPS | 494 TFLOPS | — | 700W | HBM3 |
| H100 94GB SXM (BUBB) | 989 TFLOPS | 494 TFLOPS | — | 700W | HBM2e |
Notes:
- SXM boards do NOT list FP8 peak in this table (field empty)
- fp8_e5m2 is unsupported on H100 PCIe HBM2e — confirmed in our tests
- Tensor Cores: PCIe = 456, SXM = 528 (16% more on SXM)
## Observed efficiency (H100 80GB PCIe, throttled server)
From the report in this session (power+thermal throttle throughout steady):
| Precision | Measured | Spec (dense) | % of spec |
|---|---|---|---|
| fp16_tensor | 329 TOPS | 756 TFLOPS | 44% |
| fp32_tf32 | 115 TOPS | 378 TFLOPS | 30% |
| fp8_e4m3 | 505 TOPS | 1,513 TFLOPS | 33% |
3344% of spec is expected given sustained power+thermal throttle (avg clock
1384 MHz vs boost 1755 MHz = 79%). The GPU is computing correctly for its
actual frequency — the low TOPS comes from throttle, not silicon defect.
## H200 official spec (from NVIDIA datasheet, image 24, 2026-04-06)
Format: without sparsity / with sparsity.
| Model | FP16 Tensor (dense) | TF32 (dense) | FP8 (dense) | TDP | Memory |
|---|---|---|---|---|---|
| H200 NVL PCIe | 836 TFLOPS | 418 TFLOPS | 1,570 TFLOPS | 600W | HBM3e 141GB |
| H200 SXM | 990 TFLOPS | 495 TFLOPS | 1,979 TFLOPS | 700W | HBM3e 141GB |
## Observed efficiency (H200 NVL PCIe, throttled non-designed server)
Avg clock 1635 MHz (62% of boost ~2619 MHz). Entire steady in thermal throttle.
| Precision | Measured | Spec (dense) | % of spec |
|---|---|---|---|
| fp16_tensor | 340 TOPS | 836 TFLOPS | 41% |
| fp32_tf32 | 120 TOPS | 418 TFLOPS | 29% |
| fp8_e4m3 | 529 TOPS | 1,570 TFLOPS | 34% |
Comparable to H100 PCIe efficiency (3344%) despite different architecture —
both are throttle-limited. Confirms that % of spec is not a quality signal,
it reflects the thermal environment. tops_per_sm_per_ghz is the right metric.
## Real-world GEMM efficiency reference (2026-04-06, web research)
Sources: SemiAnalysis MI300X vs H100 vs H200 training benchmark; cuBLAS optimization
worklog (hamzaelshafie.bearblog.dev); Lambda AI H100 performance analysis.
### What healthy systems actually achieve:
- H100 SXM in designed server: **~720 TFLOPS FP16 = ~73% of spec**
- cuBLAS large square GEMM (8192³): up to **~83% flop utilization**
- H200 NVL PCIe: no public data, extrapolating ~73% → ~610 TFLOPS FP16
### Our results vs expectation:
| GPU | Our FP16 | Expected (73%) | Our % of spec | Gap |
|---|---|---|---|---|
| H100 PCIe HBM2e | 329 TOPS | ~552 TFLOPS | 44% | ~1.7× below |
| H200 NVL PCIe | 340 TOPS | ~610 TFLOPS | 41% | ~1.8× below |
Our results are roughly **half** of what a healthy system achieves even under throttle.
This is NOT normal — 30-44% is not the industry baseline.
### Likely causes of the gap (in order of probability):
1. **Thermal throttle** — confirmed, sw_thermal covers entire steady window
2. **Power limit below TDP** — GPU may be software-limited below 350W/600W.
Previous user may have set a lower limit via nvidia-smi -pl and it was not
reset. Our normalization sets clock locks but does NOT reset power limit.
Key check: `nvidia-smi -q | grep "Power Limit"` — default vs enforced.
3. **Matrix size** — ruled out. bee-gpu-burn uses 4096×4096×4096 for fp16,
8192×8192×4096 for fp8. These are large enough for peak tensor utilization.
### Power limit gap analysis (H100 PCIe):
- Avg clock 1384 MHz = 79% of boost 1755 MHz
- Expected TOPS at 79% clock: 756 × 0.79 ≈ 597 TFLOPS
- Actually measured: 329 TOPS = 55% of that estimate
- Remaining gap after accounting for clock throttle: ~45%
- Most likely explanation: enforced power limit < 350W TDP, further reducing
sustainable clock beyond what sw_thermal alone would cause.
### Action item:
Add `power.limit` (enforced) AND `power.default_limit` to queryBenchmarkGPUInfo
so result.json shows if the card was pre-configured with a non-default limit.
If enforced < default × 0.95 → add finding "GPU power limit is below default TDP".
### CPU/RAM impact on GPU FLOPS:
None. Pure on-GPU GEMM is fully compute-bound once data is in VRAM.
CPU core count and host RAM are irrelevant.
## Compute efficiency metric (proposed, no hardcode)
Instead of comparing TOPS to a hardcoded spec, compute:
tops_per_sm_per_ghz = measured_tops / (sm_count × avg_clock_ghz)
This is model-agnostic. A GPU computing correctly at its actual frequency
will show a consistent tops_per_sm_per_ghz regardless of throttle level.
A GPU with degraded silicon will show low tops_per_sm_per_ghz even at
normal clocks.
SM count is queryable: nvidia-smi --query-gpu=attribute.multiprocessor_count
(needs to be added to queryBenchmarkGPUInfo).
Reference values to establish after baseline runs:
- H100 PCIe fp16_tensor: TBD tops/SM/GHz
- H100 SXM fp16_tensor: TBD tops/SM/GHz
## Proposed threshold changes (pending more data)
1. **`low_sm_clock_vs_target`**: raise threshold from 90% to 85% based on observed
9192% on healthy HBM2e. Or remove entirely — sw_power/sw_thermal already
capture the root cause.
2. **`variance_too_high`** (StabilityScore < 85): healthy HBM2e WILL oscillate
under power cap. Consider suppressing this flag when power is flat and usage
is 100% (oscillation is expected). Or lower threshold to 70.
3. **New signal: MHz/Watt efficiency**: if base_graphics_clock_mhz is available,
ratio avg_clock / power_w could identify degraded silicon (HBM3 restored S1
would have been caught by this).
Decision deferred until baseline on SXM designed servers collected.

View File

@@ -606,6 +606,20 @@ struct prepared_profile {
};
static const struct profile_desc k_profiles[] = {
{
"fp64",
"fp64",
80,
1,
0,
0,
8,
CUDA_R_64F,
CUDA_R_64F,
CUDA_R_64F,
CUDA_R_64F,
CUBLAS_COMPUTE_64F,
},
{
"fp32_tf32",
"fp32",

View File

@@ -917,6 +917,86 @@ elif [ -d "${LB_PKG_CACHE}" ] && [ "$(ls -A "${LB_PKG_CACHE}" 2>/dev/null)" ]; t
rsync -a "${LB_PKG_CACHE}/" "${BUILD_WORK_DIR}/cache/packages.chroot/"
fi
if [ "$BEE_GPU_VENDOR" != "nvidia" ] || [ "$BEE_NVIDIA_MODULE_FLAVOR" != "proprietary" ]; then
cat > "${BUILD_WORK_DIR}/config/bootloaders/grub-pc/grub.cfg" <<'EOF'
source /boot/grub/config.cfg
echo ""
echo " ███████╗ █████╗ ███████╗██╗ ██╗ ██████╗ ███████╗███████╗"
echo " ██╔════╝██╔══██╗██╔════╝╚██╗ ██╔╝ ██╔══██╗██╔════╝██╔════╝"
echo " █████╗ ███████║███████╗ ╚████╔╝ █████╗██████╔╝█████╗ █████╗"
echo " ██╔══╝ ██╔══██║╚════██║ ╚██╔╝ ╚════╝██╔══██╗██╔══╝ ██╔══╝"
echo " ███████╗██║ ██║███████║ ██║ ██████╔╝███████╗███████╗"
echo " ╚══════╝╚═╝ ╚═╝╚══════╝ ╚═╝ ╚═════╝ ╚══════╝╚══════╝"
echo " Hardware Audit LiveCD"
echo ""
menuentry "EASY-BEE" {
linux @KERNEL_LIVE@ @APPEND_LIVE@ nomodeset net.ifnames=0 biosdevname=0 mitigations=off transparent_hugepage=always numa_balancing=disable nowatchdog nosoftlockup
initrd @INITRD_LIVE@
}
submenu "EASY-BEE (advanced options) -->" {
menuentry "EASY-BEE — KMS (no nomodeset)" {
linux @KERNEL_LIVE@ @APPEND_LIVE@ net.ifnames=0 biosdevname=0 mitigations=off transparent_hugepage=always numa_balancing=disable nowatchdog nosoftlockup
initrd @INITRD_LIVE@
}
menuentry "EASY-BEE — fail-safe" {
linux @KERNEL_LIVE@ @APPEND_LIVE@ nomodeset noapic noapm nodma nomce nolapic nosmp vga=normal net.ifnames=0 biosdevname=0
initrd @INITRD_LIVE@
}
}
if [ "${grub_platform}" = "efi" ]; then
menuentry "Memory Test (memtest86+)" {
chainloader /boot/memtest86+x64.efi
}
else
menuentry "Memory Test (memtest86+)" {
linux16 /boot/memtest86+x64.bin
}
fi
if [ "${grub_platform}" = "efi" ]; then
menuentry "UEFI Firmware Settings" {
fwsetup
}
fi
EOF
cat > "${BUILD_WORK_DIR}/config/bootloaders/isolinux/live.cfg.in" <<'EOF'
label live-@FLAVOUR@-normal
menu label ^EASY-BEE
menu default
linux @LINUX@
initrd @INITRD@
append @APPEND_LIVE@
label live-@FLAVOUR@-kms
menu label EASY-BEE (^graphics/KMS)
linux @LINUX@
initrd @INITRD@
append @APPEND_LIVE@ bee.display=kms
label live-@FLAVOUR@-toram
menu label EASY-BEE (^load to RAM)
linux @LINUX@
initrd @INITRD@
append @APPEND_LIVE@ toram
label live-@FLAVOUR@-failsafe
menu label EASY-BEE (^fail-safe)
linux @LINUX@
initrd @INITRD@
append @APPEND_LIVE@ memtest noapic noapm nodma nomce nolapic nosmp vga=normal
label memtest
menu label ^Memory Test (memtest86+)
linux /boot/memtest86+x64.bin
EOF
fi
rsync -a "${OVERLAY_DIR}/" "${OVERLAY_STAGE_DIR}/"
rm -f \
"${OVERLAY_STAGE_DIR}/etc/bee-ssh-password-fallback" \

View File

@@ -5,69 +5,110 @@ echo "=== generating bee wallpaper ==="
mkdir -p /usr/share/bee
python3 - <<'PYEOF'
from PIL import Image, ImageDraw, ImageFont
from PIL import Image, ImageDraw, ImageFont, ImageFilter
import os
W, H = 1920, 1080
LOGO = """\
\u2588\u2588\u2588\u2588\u2588\u2588\u2557 \u2588\u2588\u2588\u2588\u2588\u2557 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2557\u2588\u2588\u2557 \u2588\u2588\u2557 \u2588\u2588\u2588\u2588\u2588\u2588\u2557 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2557\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2557
\u2588\u2588\u2554\u2550\u2550\u2550\u2550\u255d\u2588\u2588\u2554\u2550\u2550\u2588\u2588\u2557\u2588\u2588\u2554\u2550\u2550\u2550\u2550\u255d\u255a\u2588\u2588\u2557 \u2588\u2588\u2554\u255d \u2588\u2588\u2554\u2550\u2550\u2588\u2588\u2557\u2588\u2588\u2554\u2550\u2550\u2550\u2550\u255d\u2588\u2588\u2554\u2550\u2550\u2550\u2550\u255d
\u2588\u2588\u2588\u2588\u2588\u2557 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2551\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2557 \u255a\u2588\u2588\u2588\u2588\u2554\u255d \u2588\u2588\u2588\u2588\u2588\u2557\u2588\u2588\u2588\u2588\u2588\u2588\u2554\u255d\u2588\u2588\u2588\u2588\u2588\u2557 \u2588\u2588\u2588\u2588\u2588\u2557
\u2588\u2588\u2554\u2550\u2550\u255d \u2588\u2588\u2554\u2550\u2550\u2588\u2588\u2551\u255a\u2550\u2550\u2550\u2550\u2588\u2588\u2551 \u255a\u2588\u2588\u2554\u255d \u255a\u2550\u2550\u2550\u2550\u255d\u2588\u2588\u2554\u2550\u2550\u2588\u2588\u2557\u2588\u2588\u2554\u2550\u2550\u255d \u2588\u2588\u2554\u2550\u2550\u255d
\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2557\u2588\u2588\u2551 \u2588\u2588\u2551\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2551 \u2588\u2588\u2551 \u2588\u2588\u2588\u2588\u2588\u2588\u2554\u255d\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2557\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2557
\u255a\u2550\u2550\u2550\u2550\u2550\u2550\u255d\u255a\u2550\u255d \u255a\u2550\u255d\u255a\u2550\u2550\u2550\u2550\u2550\u2550\u255d \u255a\u2550\u255d \u255a\u2550\u2550\u2550\u2550\u2550\u255d \u255a\u2550\u2550\u2550\u2550\u2550\u2550\u255d\u255a\u2550\u2550\u2550\u2550\u2550\u2550\u255d
Hardware Audit LiveCD"""
GLYPHS = {
'E': ["11111", "10000", "11110", "10000", "10000", "10000", "11111"],
'A': ["01110", "10001", "10001", "11111", "10001", "10001", "10001"],
'S': ["01111", "10000", "10000", "01110", "00001", "00001", "11110"],
'Y': ["10001", "10001", "01010", "00100", "00100", "00100", "00100"],
'B': ["11110", "10001", "10001", "11110", "10001", "10001", "11110"],
'-': ["00000", "00000", "11111", "00000", "00000", "00000", "00000"],
}
# Find a monospace font that supports box-drawing characters
FONT_CANDIDATES = [
'/usr/share/fonts/truetype/dejavu/DejaVuSansMono.ttf',
'/usr/share/fonts/truetype/liberation/LiberationMono-Regular.ttf',
'/usr/share/fonts/truetype/freefont/FreeMono.ttf',
'/usr/share/fonts/truetype/noto/NotoMono-Regular.ttf',
TITLE = "EASY-BEE"
SUBTITLE = "Hardware Audit LiveCD"
CELL = 30
GLYPH_GAP = 18
ROW_GAP = 6
FG = (0xF6, 0xD0, 0x47)
FG_DIM = (0xD4, 0xA9, 0x1C)
SHADOW = (0x5E, 0x47, 0x05)
SUB = (0x96, 0x7A, 0x17)
BG = (0x05, 0x05, 0x05)
SUB_FONT_CANDIDATES = [
'/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf',
'/usr/share/fonts/truetype/liberation2/LiberationSans-Bold.ttf',
'/usr/share/fonts/truetype/liberation/LiberationSans-Bold.ttf',
'/usr/share/fonts/truetype/freefont/FreeSansBold.ttf',
]
font_path = None
for p in FONT_CANDIDATES:
if os.path.exists(p):
font_path = p
break
SIZE = 22
if font_path:
font_logo = ImageFont.truetype(font_path, SIZE)
font_sub = ImageFont.truetype(font_path, SIZE)
else:
font_logo = ImageFont.load_default()
font_sub = font_logo
def load_font(size):
for path in SUB_FONT_CANDIDATES:
if os.path.exists(path):
return ImageFont.truetype(path, size)
return ImageFont.load_default()
img = Image.new('RGB', (W, H), (0, 0, 0))
def glyph_width(ch):
return len(GLYPHS[ch][0])
def render_logo_mask():
width_cells = 0
for idx, ch in enumerate(TITLE):
width_cells += glyph_width(ch)
if idx != len(TITLE) - 1:
width_cells += 1
mask_w = width_cells * CELL + (len(TITLE) - 1) * GLYPH_GAP
mask_h = 7 * CELL + 6 * ROW_GAP
mask = Image.new('L', (mask_w, mask_h), 0)
draw = ImageDraw.Draw(mask)
cx = 0
for idx, ch in enumerate(TITLE):
glyph = GLYPHS[ch]
for row_idx, row in enumerate(glyph):
for col_idx, cell in enumerate(row):
if cell != '1':
continue
x0 = cx + col_idx * CELL
y0 = row_idx * (CELL + ROW_GAP)
x1 = x0 + CELL - 4
y1 = y0 + CELL - 4
draw.rounded_rectangle((x0, y0, x1, y1), radius=4, fill=255)
cx += glyph_width(ch) * CELL
if idx != len(TITLE) - 1:
cx += CELL + GLYPH_GAP
return mask
img = Image.new('RGB', (W, H), BG)
draw = ImageDraw.Draw(img)
# Measure logo block line by line to avoid font ascender offset
lines = LOGO.split('\n')
logo_lines = lines[:6]
sub_line = lines[6] if len(lines) > 6 else ''
# Soft amber glow under the logo without depending on font rendering.
glow = Image.new('RGBA', (W, H), (0, 0, 0, 0))
glow_draw = ImageDraw.Draw(glow)
glow_draw.ellipse((360, 250, 1560, 840), fill=(180, 120, 10, 56))
glow_draw.ellipse((520, 340, 1400, 760), fill=(255, 190, 40, 36))
glow = glow.filter(ImageFilter.GaussianBlur(60))
img = Image.alpha_composite(img.convert('RGBA'), glow)
line_h = SIZE + 2
block_h = len(logo_lines) * line_h + 8 + (SIZE if sub_line else 0)
logo_mask = render_logo_mask()
logo_w, logo_h = logo_mask.size
logo_x = (W - logo_w) // 2
logo_y = 290
# Width: measure the widest logo line
max_w = 0
for line in logo_lines:
bb = draw.textbbox((0, 0), line, font=font_logo)
max_w = max(max_w, bb[2] - bb[0])
shadow_mask = logo_mask.filter(ImageFilter.GaussianBlur(2))
img.paste(SHADOW, (logo_x + 16, logo_y + 14), shadow_mask)
img.paste(FG_DIM, (logo_x + 8, logo_y + 7), logo_mask)
img.paste(FG, (logo_x, logo_y), logo_mask)
x = (W - max_w) // 2
y = (H - block_h) // 2
font_sub = load_font(30)
sub_bb = draw.textbbox((0, 0), SUBTITLE, font=font_sub)
sub_x = (W - (sub_bb[2] - sub_bb[0])) // 2
sub_y = logo_y + logo_h + 54
draw = ImageDraw.Draw(img)
draw.text((sub_x + 2, sub_y + 2), SUBTITLE, font=font_sub, fill=(35, 28, 6))
draw.text((sub_x, sub_y), SUBTITLE, font=font_sub, fill=SUB)
cy = y
for line in logo_lines:
draw.text((x, cy), line, font=font_logo, fill=(0xf6, 0xc9, 0x0e))
cy += line_h
cy += 8
if sub_line:
draw.text((x, cy), sub_line, font=font_sub, fill=(0x80, 0x68, 0x18))
img = img.convert('RGB')
img.save('/usr/share/bee/wallpaper.png', optimize=True)
print('wallpaper written: /usr/share/bee/wallpaper.png')

View File

@@ -0,0 +1,41 @@
#!/bin/sh
# 9010-fix-toram.hook.chroot — patch live-boot toram to work with tmpfs (no O_DIRECT)
#
# live-boot tries "losetup --replace --direct-io=on" when re-associating the
# loop device to the RAM copy in /dev/shm. tmpfs does not support O_DIRECT,
# so the ioctl returns EINVAL and the verification step fails.
#
# The patch replaces the replace call so that if --direct-io=on fails it falls
# back to a plain replace without direct-io, and also relaxes the verification
# to a warning so the boot continues even when re-association is imperfect.
set -e
TORAM_SCRIPT="/usr/lib/live/boot/9990-toram-todisk.sh"
if [ ! -f "${TORAM_SCRIPT}" ]; then
echo "9010-fix-toram: ${TORAM_SCRIPT} not found, skipping"
exit 0
fi
echo "9010-fix-toram: patching ${TORAM_SCRIPT}"
# Replace any losetup --replace call that includes --direct-io=on with a
# version that first tries with direct-io, then retries without it.
#
# The sed expression turns:
# losetup --replace ... --direct-io=on LOOP FILE
# into a shell snippet that tries both, silently.
#
# We also downgrade the fatal "Task finished with error." block to a warning
# so the boot continues if re-association fails (squashfs still accessible).
# 1. Strip --direct-io=on from the losetup --replace call so it works on tmpfs.
sed -i 's/losetup --replace --direct-io=on/losetup --replace/g' "${TORAM_SCRIPT}"
sed -i 's/losetup --replace --direct-io/losetup --replace/g' "${TORAM_SCRIPT}"
# 2. Turn the hard error into a warning so boot continues.
# live-boot prints this exact string when verification fails.
sed -i 's/echo "Task finished with error\."/echo "Warning: toram re-association failed, continuing boot (squashfs still in RAM)"/' "${TORAM_SCRIPT}"
echo "9010-fix-toram: patch applied"
grep -n "losetup" "${TORAM_SCRIPT}" | head -20 || true

View File

@@ -27,6 +27,7 @@ echo ""
KVER=$(uname -r)
info "kernel: $KVER"
NVIDIA_BOOT_MODE="normal"
NVIDIA_MODULES_FLAVOR="proprietary"
for arg in $(cat /proc/cmdline 2>/dev/null); do
case "$arg" in
bee.nvidia.mode=*)
@@ -34,7 +35,11 @@ for arg in $(cat /proc/cmdline 2>/dev/null); do
;;
esac
done
if [ -f /etc/bee-nvidia-modules-flavor ]; then
NVIDIA_MODULES_FLAVOR="$(tr -d '[:space:]' </etc/bee-nvidia-modules-flavor 2>/dev/null || echo proprietary)"
fi
info "nvidia boot mode: ${NVIDIA_BOOT_MODE}"
info "nvidia modules flavor: ${NVIDIA_MODULES_FLAVOR}"
# --- PATH & binaries ---
echo "-- PATH & binaries --"
@@ -110,10 +115,12 @@ fi
for mod in nvidia_modeset nvidia_uvm; do
if /sbin/lsmod 2>/dev/null | grep -q "^$mod "; then
ok "module loaded: $mod"
elif [ "${NVIDIA_BOOT_MODE}" = "normal" ] || [ "${NVIDIA_BOOT_MODE}" = "full" ]; then
elif [ "${NVIDIA_MODULES_FLAVOR}" = "proprietary" ] && { [ "${NVIDIA_BOOT_MODE}" = "normal" ] || [ "${NVIDIA_BOOT_MODE}" = "full" ]; }; then
fail "module NOT loaded in normal mode: $mod"
else
elif [ "${NVIDIA_MODULES_FLAVOR}" = "proprietary" ]; then
warn "module not loaded in GSP-off mode: $mod"
else
fail "module NOT loaded: $mod"
fi
done
@@ -129,10 +136,12 @@ done
if [ -e /dev/nvidia-uvm ]; then
ok "/dev/nvidia-uvm exists"
elif [ "${NVIDIA_BOOT_MODE}" = "normal" ] || [ "${NVIDIA_BOOT_MODE}" = "full" ]; then
elif [ "${NVIDIA_MODULES_FLAVOR}" = "proprietary" ] && { [ "${NVIDIA_BOOT_MODE}" = "normal" ] || [ "${NVIDIA_BOOT_MODE}" = "full" ]; }; then
fail "/dev/nvidia-uvm missing in normal mode"
else
elif [ "${NVIDIA_MODULES_FLAVOR}" = "proprietary" ]; then
warn "/dev/nvidia-uvm missing — CUDA stress path may be unavailable until loaded on demand"
else
fail "/dev/nvidia-uvm missing"
fi
echo ""

View File

@@ -6,6 +6,19 @@ NVIDIA_KO_DIR="/usr/local/lib/nvidia"
log() { echo "[bee-nvidia] $*"; }
read_nvidia_modules_flavor() {
if [ -f /etc/bee-nvidia-modules-flavor ]; then
flavor="$(tr -d '[:space:]' </etc/bee-nvidia-modules-flavor 2>/dev/null)"
case "$flavor" in
open|proprietary)
echo "$flavor"
return 0
;;
esac
fi
echo "proprietary"
}
log "kernel: $(uname -r)"
# Skip if no NVIDIA GPU present (PCI vendor 10de)
@@ -40,6 +53,8 @@ if [ -z "$nvidia_mode" ]; then
nvidia_mode="normal"
fi
log "boot mode: $nvidia_mode"
nvidia_modules_flavor="$(read_nvidia_modules_flavor)"
log "modules flavor: $nvidia_modules_flavor"
load_module() {
mod="$1"
@@ -150,37 +165,54 @@ load_host_module() {
return 1
}
case "$nvidia_mode" in
normal|full)
if ! load_module_with_gsp_fallback; then
exit 1
fi
# nvidia-modeset on some server kernels needs ACPI video helper symbols
# exported by the generic "video" module. Best-effort only; compute paths
# remain functional even if display-related modules stay absent.
load_host_module video || true
load_module nvidia-modeset || true
load_module nvidia-uvm || true
;;
gsp-off|safe)
# NVIDIA documents that GSP firmware is enabled by default on newer GPUs and can
# be disabled via NVreg_EnableGpuFirmware=0. Safe mode keeps the live ISO on the
# conservative path for platforms where full boot-time GSP init is unstable.
if ! load_module nvidia NVreg_EnableGpuFirmware=0; then
exit 1
fi
log "GSP-off mode: skipping nvidia-modeset and nvidia-uvm during boot"
;;
nomsi|*)
# nomsi: disable MSI-X/MSI interrupts — use when RmInitAdapter fails with
# "Failed to enable MSI-X" on one or more GPUs (IOMMU group interrupt limits).
# NVreg_EnableMSI=0 forces legacy INTx interrupts for all GPUs.
if ! load_module nvidia NVreg_EnableGpuFirmware=0 NVreg_EnableMSI=0; then
exit 1
fi
log "nomsi mode: MSI-X disabled (NVreg_EnableMSI=0), skipping nvidia-modeset and nvidia-uvm"
;;
esac
if [ "$nvidia_modules_flavor" = "open" ]; then
case "$nvidia_mode" in
gsp-off|safe|nomsi)
log "ignoring boot mode ${nvidia_mode} for open NVIDIA modules"
;;
esac
if ! load_module nvidia; then
exit 1
fi
# nvidia-modeset on some server kernels needs ACPI video helper symbols
# exported by the generic "video" module. Best-effort only; compute paths
# remain functional even if display-related modules stay absent.
load_host_module video || true
load_module nvidia-modeset || true
load_module nvidia-uvm || true
else
case "$nvidia_mode" in
normal|full)
if ! load_module_with_gsp_fallback; then
exit 1
fi
# nvidia-modeset on some server kernels needs ACPI video helper symbols
# exported by the generic "video" module. Best-effort only; compute paths
# remain functional even if display-related modules stay absent.
load_host_module video || true
load_module nvidia-modeset || true
load_module nvidia-uvm || true
;;
gsp-off|safe)
# NVIDIA documents that GSP firmware is enabled by default on newer GPUs and can
# be disabled via NVreg_EnableGpuFirmware=0. Safe mode keeps the live ISO on the
# conservative path for platforms where full boot-time GSP init is unstable.
if ! load_module nvidia NVreg_EnableGpuFirmware=0; then
exit 1
fi
log "GSP-off mode: skipping nvidia-modeset and nvidia-uvm during boot"
;;
nomsi|*)
# nomsi: disable MSI-X/MSI interrupts — use when RmInitAdapter fails with
# "Failed to enable MSI-X" on one or more GPUs (IOMMU group interrupt limits).
# NVreg_EnableMSI=0 forces legacy INTx interrupts for all GPUs.
if ! load_module nvidia NVreg_EnableGpuFirmware=0 NVreg_EnableMSI=0; then
exit 1
fi
log "nomsi mode: MSI-X disabled (NVreg_EnableMSI=0), skipping nvidia-modeset and nvidia-uvm"
;;
esac
fi
# Create /dev/nvidia* device nodes (udev rules absent since we use .run installer)
nvidia_major=$(grep -m1 ' nvidiactl$' /proc/devices | awk '{print $1}')