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28 Commits

Author SHA1 Message Date
Mikhail Chusavitin
5285c0d101 Capture per-run IPMI power and GPU telemetry in power benchmark
- Sample IPMI loaded_w per single-card calibration and per ramp step
  instead of averaging over the entire Phase 2; top-level ServerPower
  uses the final (all-GPU) ramp step value
- Add ServerLoadedW/ServerDeltaW to NvidiaPowerBenchGPU and
  NvidiaPowerBenchStep so external tooling can compare wall power per
  phase without re-parsing logs
- Write gpu-metrics.csv/.html inside each single-XX/ and step-XX/
  subdir; aggregate all phases into a top-level gpu-metrics.csv/.html
- Write 00-nvidia-smi-q.log at the start of every power run
- Add Telemetry (p95 temp/power/fan/clock) to NvidiaPowerBenchGPU in
  result.json from the converged calibration attempt
- Power benchmark page: split "Achieved W" into Single-card W and
  Multi-GPU W (StablePowerLimitW); derate highlight and status color
  now reflect the final multi-GPU limit vs nominal
- Performance benchmark page: add Status column and per-GPU score
  color coding (green/yellow/red) based on gpu.Status and OverallStatus

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-17 17:59:58 +03:00
Mikhail Chusavitin
dca4afb8d0 Seed power ramp with single-card TDP limits 2026-04-16 11:43:01 +03:00
Mikhail Chusavitin
b4280941f5 Move NCCL and NVBandwidth into validate mode 2026-04-16 11:02:30 +03:00
Mikhail Chusavitin
f74976ec4c Use static overlay wallpaper in ISO build 2026-04-16 10:54:03 +03:00
Mikhail Chusavitin
18e24a9aa5 Estimate fan duty from observed RPM maxima 2026-04-16 10:10:18 +03:00
Mikhail Chusavitin
e306250da7 Disable fp64/fp4 in mixed gpu burn 2026-04-16 10:00:03 +03:00
Mikhail Chusavitin
c5b2081ac9 Disable unstable fp4/fp64 benchmark phases 2026-04-16 09:58:02 +03:00
434528083e Power bench: compare GPU-reported TDP vs IPMI server power delta
- NvidiaPowerBenchResult gains ServerPower *BenchmarkServerPower
- RunNvidiaPowerBench samples IPMI idle before Phase 1 and loaded via
  background goroutine throughout Phase 2 ramp
- renderPowerBenchReport: new "Server vs GPU Power Comparison" table
  with ratio annotation (✓ match / ⚠ minor / ✗ over-report)
- renderPowerBenchSummary: server_idle_w, server_loaded_w, server_delta_w,
  server_reporting_ratio keys

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-16 07:21:02 +03:00
30aa30cd67 LiveCD: set Baby Bee wallpaper centered on black background
400×400px PNG centered via feh --bg-center --image-bg '#000000'.
Fallback solid fill also changed to black.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-16 06:57:23 +03:00
4f76e1de21 Dashboard: per-device status chips with hover tooltips
Replace single aggregated badge per hardware category with individual
colored chips (O/W/F/?) for each ComponentStatusRecord. Added helper
functions: matchedRecords, firstNonEmpty. CSS classes: chip-ok/warn/fail/unknown.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-16 06:54:13 +03:00
3732e64a4a Add slowdown temperature exceedance detector to benchmark
detectSlowdownTempExceedance scans steady-state metric rows per GPU and
emits a [WARNING] note + PARTIAL status if any sample >= SlowdownTempC.
Uses per-GPU threshold from nvidia-smi -q, fallback 80°C.

Distinct from p95-based TempHeadroomC check: catches even a single spike
above the slowdown threshold that would be smoothed out in aggregates.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-16 06:46:45 +03:00
0d925299ff Use per-GPU temperature limits from nvidia-smi -q for headroom calculation
Parse "GPU Shutdown Temp" and "GPU Slowdown Temp" from nvidia-smi -q verbose
output in enrichGPUInfoWithMaxClocks. Store as ShutdownTempC/SlowdownTempC
on benchmarkGPUInfo and BenchmarkGPUResult. Fallback: 90°C shutdown / 80°C
slowdown when not available.

TempHeadroomC = ShutdownTempC - P95TempC (per-GPU, not hardcoded 100°C).
Warning threshold: p95 >= SlowdownTempC. Critical: headroom < 10°C.
Report table shows both limits alongside headroom and p95 temp.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-16 06:45:15 +03:00
a8d5e019a5 Translate report to English; add power anomaly detector
All report strings are now English only.

Add detectPowerAnomaly: scans steady-state metric rows per GPU with a
5-sample rolling baseline; flags a sudden drop ≥30% while GPU usage >50%
as [HARD STOP] — indicates bad cable contact or VRM fault.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-16 06:42:00 +03:00
72ec086568 Restructure benchmark report as balanced scorecard (5 perspectives)
Split throttle into separate signals: ThermalThrottlePct, PowerCapThrottlePct,
SyncBoostThrottlePct. Add TempHeadroomC (100 - p95_temp) as independent
thermal headroom metric; warning < 20°C (>80°C), critical < 10°C (>90°C).

Hard stop findings: thermal throttle with fans < 95%, ECC uncorrected errors,
p95 temp > 90°C. Throttle findings now include per-type percentages and
diagnostic context.

Replace flat scorecard table with BSC 5-perspective layout:
1. Compatibility (hard stops: thermal+fan, ECC)
2. Thermal headroom (p95 temp, delta to 100°C, throttle %)
3. Power delivery (power cap throttle, power CV, fan duty)
4. Performance (Compute TOPS, Synthetic, Mixed, TOPS/SM/GHz)
5. Anomalies (ECC corrected, sync boost, power/thermal variance)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-16 06:40:06 +03:00
7a0b0934df Separate compute score from server quality score
CompositeScore = raw ComputeScore (TOPS). Throttling GPUs score lower
automatically — no quality multiplier distorting the compute signal.

Add ServerQualityScore (0-100): server infrastructure quality independent
of GPU model. Formula: 0.40×Stability + 0.30×PowerSustain + 0.30×Thermal.
Use to compare servers with the same GPU or flag bad server conditions.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-16 00:45:55 +03:00
d8ca0dca2c Redesign scoring metrics: variance-based sustain scores, throttle stability
PowerSustainScore: power draw variance (CV) during load, not deviation from TDP.
ThermalSustainScore: temperature variance (CV) during load.
StabilityScore: fraction of time spent in thermal+power-cap throttling.
Remove NCCL bonus from quality_factor.

quality = 0.35 + 0.35×Stability + 0.15×PowerSustain + 0.15×ThermalSustain, cap 1.00.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-16 00:39:59 +03:00
d90250f80a Fix DCGM cleanup and shorten memory validate 2026-04-16 00:39:37 +03:00
8d6eaef5de Update perf benchmark report methodology to reflect new design
Remove references to pre-benchmark power calibration and dcgmi
targeted_power. Document platform_power_score ramp-up methodology,
PowerSustainScore fallback to steady-state power, and full-budget
single-precision phases.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-16 00:31:58 +03:00
732bf4cbab Redesign power and performance benchmarks with new methodology
Power/Thermal Fit: cumulative fixed-limit ramp where each GPU's stable TDP
is found under real multi-GPU thermal load (all prior GPUs running at their
fixed limits). PlatformMaxTDPW = sum of stable limits across all GPUs.
Remove PlatformPowerScore from power test.

Performance Benchmark: remove pre-benchmark power calibration entirely.
After N single-card runs, execute k=2..N parallel ramp-up steps and compute
PlatformPowerScore = mean compute scalability vs best single-card TOPS.
PowerSustainScore falls back to Steady.AvgPowerW when calibration absent.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-16 00:30:50 +03:00
fa6d905a10 Tune bee-gpu-burn single-precision benchmark phases 2026-04-16 00:05:47 +03:00
Mikhail Chusavitin
5c1862ce4c Use lb clean --all to clear bootstrap cache on every build
Prevents stale debootstrap cache from bypassing --debootstrap-options
changes (e.g. --include=ca-certificates added in v8.15).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-15 17:37:08 +03:00
Mikhail Chusavitin
b65ef2ea1d Fix: use --debootstrap-options to include ca-certificates in bootstrap
--bootstrap-packages is not a valid lb config option (20230502).
Use --debootstrap-options "--include=ca-certificates" instead to ensure
ca-certificates is present when lb chroot_archives runs apt-get update
against the NVIDIA CUDA HTTPS source.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-15 17:26:01 +03:00
Mikhail Chusavitin
533d703c97 Bootstrap ca-certificates so NVIDIA CUDA HTTPS source is trusted
debootstrap creates a minimal chroot without ca-certificates, causing
apt-get update to fail TLS verification for the NVIDIA CUDA apt source:
  "No system certificates available. Try installing ca-certificates."
Add ca-certificates to --bootstrap-packages so it is present before
lb chroot_archives configures the NVIDIA HTTPS source and runs apt-get update.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-15 17:24:20 +03:00
Mikhail Chusavitin
04eb4b5a6d Revert "Pre-download DCGM/fabricmanager debs on host to bypass chroot apt"
This reverts commit 4110dbf8a6.
2026-04-15 17:19:53 +03:00
Mikhail Chusavitin
4110dbf8a6 Pre-download DCGM/fabricmanager debs on host to bypass chroot apt
The NVIDIA CUDA HTTPS apt source (developer.download.nvidia.com) may be
unreachable from inside the live-build container chroot, causing
'E: Unable to locate package datacenter-gpu-manager-4-cuda13'.

Add build-dcgm.sh that downloads DCGM and nvidia-fabricmanager .deb
packages on the build host (verifying SHA256 against Packages.gz) and
caches them in BEE_CACHE_DIR.  build.sh (step 25-dcgm, nvidia only)
copies them into LB_DIR/config/packages.chroot/ before lb build, so
live-build creates a local apt repo from them.  The chroot installs the
packages from the local repo without ever contacting the NVIDIA CUDA
HTTPS source.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-15 17:10:23 +03:00
Mikhail Chusavitin
7237e4d3e4 Add fabric manager boot and support diagnostics 2026-04-15 16:14:26 +03:00
Mikhail Chusavitin
ab3ad77cd6 Fix Go module: upgrade modernc.org/libc v1.70.0 → v1.72.0
modernc.org/sqlite v1.48.0 requires modernc.org/libc/sys/types which is
absent in v1.70.0 but present in v1.72.0.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-15 14:32:04 +03:00
Mikhail Chusavitin
cd9e2cbe13 Fix ramp-up power bench: one task instead of N redundant tasks
RunNvidiaPowerBench already performs a full internal ramp from 1 to N
GPUs in Phase 2. Spawning N tasks with growing GPU subsets meant task K
repeated all steps 1..K-1 already done by tasks 1..K-1 — O(N²) work
instead of O(N). Replace with a single task using all selected GPUs.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-15 12:29:11 +03:00
30 changed files with 1931 additions and 646 deletions

View File

@@ -5,22 +5,18 @@ go 1.25.0
replace reanimator/chart => ../internal/chart
require (
github.com/go-analyze/charts v0.5.26
modernc.org/sqlite v1.48.0
reanimator/chart v0.0.0-00010101000000-000000000000
)
require (
github.com/dustin/go-humanize v1.0.1 // indirect
github.com/go-analyze/bulk v0.1.3 // indirect
github.com/golang/freetype v0.0.0-20170609003504-e2365dfdc4a0 // indirect
github.com/google/uuid v1.6.0 // indirect
github.com/mattn/go-isatty v0.0.20 // indirect
github.com/ncruces/go-strftime v1.0.0 // indirect
github.com/remyoudompheng/bigfft v0.0.0-20230129092748-24d4a6f8daec // indirect
golang.org/x/image v0.24.0 // indirect
golang.org/x/sys v0.42.0 // indirect
modernc.org/libc v1.70.0 // indirect
modernc.org/libc v1.72.0 // indirect
modernc.org/mathutil v1.7.1 // indirect
modernc.org/memory v1.11.0 // indirect
modernc.org/sqlite v1.48.0 // indirect
)

View File

@@ -1,37 +1,51 @@
github.com/davecgh/go-spew v1.1.1 h1:vj9j/u1bqnvCEfJOwUhtlOARqs3+rkHYY13jYWTU97c=
github.com/davecgh/go-spew v1.1.1/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
github.com/dustin/go-humanize v1.0.1 h1:GzkhY7T5VNhEkwH0PVJgjz+fX1rhBrR7pRT3mDkpeCY=
github.com/dustin/go-humanize v1.0.1/go.mod h1:Mu1zIs6XwVuF/gI1OepvI0qD18qycQx+mFykh5fBlto=
github.com/go-analyze/bulk v0.1.3 h1:pzRdBqzHDAT9PyROt0SlWE0YqPtdmTcEpIJY0C3vF0c=
github.com/go-analyze/bulk v0.1.3/go.mod h1:afon/KtFJYnekIyN20H/+XUvcLFjE8sKR1CfpqfClgM=
github.com/go-analyze/charts v0.5.26 h1:rSwZikLQuFX6cJzwI8OAgaWZneG1kDYxD857ms00ZxY=
github.com/go-analyze/charts v0.5.26/go.mod h1:s1YvQhjiSwtLx1f2dOKfiV9x2TT49nVSL6v2rlRpTbY=
github.com/golang/freetype v0.0.0-20170609003504-e2365dfdc4a0 h1:DACJavvAHhabrF08vX0COfcOBJRhZ8lUbR+ZWIs0Y5g=
github.com/golang/freetype v0.0.0-20170609003504-e2365dfdc4a0/go.mod h1:E/TSTwGwJL78qG/PmXZO1EjYhfJinVAhrmmHX6Z8B9k=
github.com/google/pprof v0.0.0-20250317173921-a4b03ec1a45e h1:ijClszYn+mADRFY17kjQEVQ1XRhq2/JR1M3sGqeJoxs=
github.com/google/pprof v0.0.0-20250317173921-a4b03ec1a45e/go.mod h1:boTsfXsheKC2y+lKOCMpSfarhxDeIzfZG1jqGcPl3cA=
github.com/google/uuid v1.6.0 h1:NIvaJDMOsjHA8n1jAhLSgzrAzy1Hgr+hNrb57e+94F0=
github.com/google/uuid v1.6.0/go.mod h1:TIyPZe4MgqvfeYDBFedMoGGpEw/LqOeaOT+nhxU+yHo=
github.com/hashicorp/golang-lru/v2 v2.0.7 h1:a+bsQ5rvGLjzHuww6tVxozPZFVghXaHOwFs4luLUK2k=
github.com/hashicorp/golang-lru/v2 v2.0.7/go.mod h1:QeFd9opnmA6QUJc5vARoKUSoFhyfM2/ZepoAG6RGpeM=
github.com/mattn/go-isatty v0.0.20 h1:xfD0iDuEKnDkl03q4limB+vH+GxLEtL/jb4xVJSWWEY=
github.com/mattn/go-isatty v0.0.20/go.mod h1:W+V8PltTTMOvKvAeJH7IuucS94S2C6jfK/D7dTCTo3Y=
github.com/ncruces/go-strftime v1.0.0 h1:HMFp8mLCTPp341M/ZnA4qaf7ZlsbTc+miZjCLOFAw7w=
github.com/ncruces/go-strftime v1.0.0/go.mod h1:Fwc5htZGVVkseilnfgOVb9mKy6w1naJmn9CehxcKcls=
github.com/pmezard/go-difflib v1.0.0 h1:4DBwDE0NGyQoBHbLQYPwSUPoCMWR5BEzIk/f1lZbAQM=
github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4=
github.com/remyoudompheng/bigfft v0.0.0-20230129092748-24d4a6f8daec h1:W09IVJc94icq4NjY3clb7Lk8O1qJ8BdBEF8z0ibU0rE=
github.com/remyoudompheng/bigfft v0.0.0-20230129092748-24d4a6f8daec/go.mod h1:qqbHyh8v60DhA7CoWK5oRCqLrMHRGoxYCSS9EjAz6Eo=
github.com/stretchr/testify v1.11.1 h1:7s2iGBzp5EwR7/aIZr8ao5+dra3wiQyKjjFuvgVKu7U=
github.com/stretchr/testify v1.11.1/go.mod h1:wZwfW3scLgRK+23gO65QZefKpKQRnfz6sD981Nm4B6U=
golang.org/x/image v0.24.0 h1:AN7zRgVsbvmTfNyqIbbOraYL8mSwcKncEj8ofjgzcMQ=
golang.org/x/image v0.24.0/go.mod h1:4b/ITuLfqYq1hqZcjofwctIhi7sZh2WaCjvsBNjjya8=
golang.org/x/mod v0.33.0 h1:tHFzIWbBifEmbwtGz65eaWyGiGZatSrT9prnU8DbVL8=
golang.org/x/mod v0.33.0/go.mod h1:swjeQEj+6r7fODbD2cqrnje9PnziFuw4bmLbBZFrQ5w=
golang.org/x/sync v0.20.0 h1:e0PTpb7pjO8GAtTs2dQ6jYa5BWYlMuX047Dco/pItO4=
golang.org/x/sync v0.20.0/go.mod h1:9xrNwdLfx4jkKbNva9FpL6vEN7evnE43NNNJQ2LF3+0=
golang.org/x/sys v0.6.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.42.0 h1:omrd2nAlyT5ESRdCLYdm3+fMfNFE/+Rf4bDIQImRJeo=
golang.org/x/sys v0.42.0/go.mod h1:4GL1E5IUh+htKOUEOaiffhrAeqysfVGipDYzABqnCmw=
gopkg.in/yaml.v3 v3.0.1 h1:fxVm/GzAzEWqLHuvctI91KS9hhNmmWOoWu0XTYJS7CA=
gopkg.in/yaml.v3 v3.0.1/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
modernc.org/libc v1.70.0 h1:U58NawXqXbgpZ/dcdS9kMshu08aiA6b7gusEusqzNkw=
modernc.org/libc v1.70.0/go.mod h1:OVmxFGP1CI/Z4L3E0Q3Mf1PDE0BucwMkcXjjLntvHJo=
golang.org/x/tools v0.42.0 h1:uNgphsn75Tdz5Ji2q36v/nsFSfR/9BRFvqhGBaJGd5k=
golang.org/x/tools v0.42.0/go.mod h1:Ma6lCIwGZvHK6XtgbswSoWroEkhugApmsXyrUmBhfr0=
modernc.org/cc/v4 v4.27.3 h1:uNCgn37E5U09mTv1XgskEVUJ8ADKpmFMPxzGJ0TSo+U=
modernc.org/cc/v4 v4.27.3/go.mod h1:3YjcbCqhoTTHPycJDRl2WZKKFj0nwcOIPBfEZK0Hdk8=
modernc.org/ccgo/v4 v4.32.4 h1:L5OB8rpEX4ZsXEQwGozRfJyJSFHbbNVOoQ59DU9/KuU=
modernc.org/ccgo/v4 v4.32.4/go.mod h1:lY7f+fiTDHfcv6YlRgSkxYfhs+UvOEEzj49jAn2TOx0=
modernc.org/fileutil v1.4.0 h1:j6ZzNTftVS054gi281TyLjHPp6CPHr2KCxEXjEbD6SM=
modernc.org/fileutil v1.4.0/go.mod h1:EqdKFDxiByqxLk8ozOxObDSfcVOv/54xDs/DUHdvCUU=
modernc.org/gc/v2 v2.6.5 h1:nyqdV8q46KvTpZlsw66kWqwXRHdjIlJOhG6kxiV/9xI=
modernc.org/gc/v2 v2.6.5/go.mod h1:YgIahr1ypgfe7chRuJi2gD7DBQiKSLMPgBQe9oIiito=
modernc.org/gc/v3 v3.1.2 h1:ZtDCnhonXSZexk/AYsegNRV1lJGgaNZJuKjJSWKyEqo=
modernc.org/gc/v3 v3.1.2/go.mod h1:HFK/6AGESC7Ex+EZJhJ2Gni6cTaYpSMmU/cT9RmlfYY=
modernc.org/goabi0 v0.2.0 h1:HvEowk7LxcPd0eq6mVOAEMai46V+i7Jrj13t4AzuNks=
modernc.org/goabi0 v0.2.0/go.mod h1:CEFRnnJhKvWT1c1JTI3Avm+tgOWbkOu5oPA8eH8LnMI=
modernc.org/libc v1.72.0 h1:IEu559v9a0XWjw0DPoVKtXpO2qt5NVLAnFaBbjq+n8c=
modernc.org/libc v1.72.0/go.mod h1:tTU8DL8A+XLVkEY3x5E/tO7s2Q/q42EtnNWda/L5QhQ=
modernc.org/mathutil v1.7.1 h1:GCZVGXdaN8gTqB1Mf/usp1Y/hSqgI2vAGGP4jZMCxOU=
modernc.org/mathutil v1.7.1/go.mod h1:4p5IwJITfppl0G4sUEDtCr4DthTaT47/N3aT6MhfgJg=
modernc.org/memory v1.11.0 h1:o4QC8aMQzmcwCK3t3Ux/ZHmwFPzE6hf2Y5LbkRs+hbI=
modernc.org/memory v1.11.0/go.mod h1:/JP4VbVC+K5sU2wZi9bHoq2MAkCnrt2r98UGeSK7Mjw=
modernc.org/opt v0.1.4 h1:2kNGMRiUjrp4LcaPuLY2PzUfqM/w9N23quVwhKt5Qm8=
modernc.org/opt v0.1.4/go.mod h1:03fq9lsNfvkYSfxrfUhZCWPk1lm4cq4N+Bh//bEtgns=
modernc.org/sortutil v1.2.1 h1:+xyoGf15mM3NMlPDnFqrteY07klSFxLElE2PVuWIJ7w=
modernc.org/sortutil v1.2.1/go.mod h1:7ZI3a3REbai7gzCLcotuw9AC4VZVpYMjDzETGsSMqJE=
modernc.org/sqlite v1.48.0 h1:ElZyLop3Q2mHYk5IFPPXADejZrlHu7APbpB0sF78bq4=
modernc.org/sqlite v1.48.0/go.mod h1:hWjRO6Tj/5Ik8ieqxQybiEOUXy0NJFNp2tpvVpKlvig=
modernc.org/strutil v1.2.1 h1:UneZBkQA+DX2Rp35KcM69cSsNES9ly8mQWD71HKlOA0=
modernc.org/strutil v1.2.1/go.mod h1:EHkiggD70koQxjVdSBM3JKM7k6L0FbGE5eymy9i3B9A=
modernc.org/token v1.1.0 h1:Xl7Ap9dKaEs5kLoOQeQmPWevfnk/DM5qcLcYlA8ys6Y=
modernc.org/token v1.1.0/go.mod h1:UGzOrNV1mAFSEB63lOFHIpNRUVMvYTc6yu1SMY/XTDM=

View File

@@ -146,7 +146,7 @@ type satRunner interface {
RunSATStressPack(ctx context.Context, baseDir string, durationSec int, logFunc func(string)) (string, error)
RunFanStressTest(ctx context.Context, baseDir string, opts platform.FanStressOptions) (string, error)
RunPlatformStress(ctx context.Context, baseDir string, opts platform.PlatformStressOptions, logFunc func(string)) (string, error)
RunNCCLTests(ctx context.Context, baseDir string, logFunc func(string)) (string, error)
RunNCCLTests(ctx context.Context, baseDir string, gpuIndices []int, logFunc func(string)) (string, error)
}
type runtimeChecker interface {
@@ -744,8 +744,15 @@ func (a *App) RunPlatformStress(ctx context.Context, baseDir string, opts platfo
return a.sat.RunPlatformStress(ctx, baseDir, opts, logFunc)
}
func (a *App) RunNCCLTests(ctx context.Context, baseDir string, gpuIndices []int, logFunc func(string)) (string, error) {
if strings.TrimSpace(baseDir) == "" {
baseDir = DefaultSATBaseDir
}
return a.sat.RunNCCLTests(ctx, baseDir, gpuIndices, logFunc)
}
func (a *App) RunNCCLTestsResult(ctx context.Context) (ActionResult, error) {
path, err := a.sat.RunNCCLTests(ctx, DefaultSATBaseDir, nil)
path, err := a.RunNCCLTests(ctx, DefaultSATBaseDir, nil, nil)
body := "Results: " + path
if err != nil && err != context.Canceled {
body += "\nERROR: " + err.Error()

View File

@@ -128,6 +128,7 @@ type fakeSAT struct {
runNvidiaPowerFn func(string, int, []int) (string, error)
runNvidiaPulseFn func(string, int, []int) (string, error)
runNvidiaBandwidthFn func(string, []int) (string, error)
runNCCLFn func(string, []int) (string, error)
runNvidiaTargetedStressFn func(string, int, []int) (string, error)
runMemoryFn func(string) (string, error)
runStorageFn func(string) (string, error)
@@ -287,10 +288,43 @@ func (f fakeSAT) RunPlatformStress(_ context.Context, _ string, _ platform.Platf
return "", nil
}
func (f fakeSAT) RunNCCLTests(_ context.Context, _ string, _ func(string)) (string, error) {
func (f fakeSAT) RunNCCLTests(_ context.Context, baseDir string, gpuIndices []int, _ func(string)) (string, error) {
if f.runNCCLFn != nil {
return f.runNCCLFn(baseDir, gpuIndices)
}
return "", nil
}
func TestRunNCCLTestsPassesSelectedGPUs(t *testing.T) {
t.Parallel()
var gotBaseDir string
var gotGPUIndices []int
a := &App{
sat: fakeSAT{
runNCCLFn: func(baseDir string, gpuIndices []int) (string, error) {
gotBaseDir = baseDir
gotGPUIndices = append([]int(nil), gpuIndices...)
return "/tmp/nccl-tests.tar.gz", nil
},
},
}
path, err := a.RunNCCLTests(context.Background(), "/tmp/sat", []int{3, 1}, nil)
if err != nil {
t.Fatalf("RunNCCLTests error: %v", err)
}
if path != "/tmp/nccl-tests.tar.gz" {
t.Fatalf("path=%q want %q", path, "/tmp/nccl-tests.tar.gz")
}
if gotBaseDir != "/tmp/sat" {
t.Fatalf("baseDir=%q want %q", gotBaseDir, "/tmp/sat")
}
if len(gotGPUIndices) != 2 || gotGPUIndices[0] != 3 || gotGPUIndices[1] != 1 {
t.Fatalf("gpuIndices=%v want [3 1]", gotGPUIndices)
}
}
func TestNetworkStatusFormatsInterfacesAndRoute(t *testing.T) {
t.Parallel()

View File

@@ -22,6 +22,8 @@ var supportBundleServices = []string{
"bee-selfheal.service",
"bee-selfheal.timer",
"bee-sshsetup.service",
"nvidia-dcgm.service",
"nvidia-fabricmanager.service",
}
var supportBundleCommands = []struct {
@@ -48,6 +50,43 @@ else
fi
`}},
{name: "system/nvidia-smi-q.txt", cmd: []string{"nvidia-smi", "-q"}},
{name: "system/nvidia-smi-topo.txt", cmd: []string{"sh", "-c", `
if command -v nvidia-smi >/dev/null 2>&1; then
nvidia-smi topo -m 2>&1 || true
else
echo "nvidia-smi not found"
fi
`}},
{name: "system/systemctl-nvidia-units.txt", cmd: []string{"sh", "-c", `
if ! command -v systemctl >/dev/null 2>&1; then
echo "systemctl not found"
exit 0
fi
echo "=== unit files ==="
systemctl list-unit-files --no-pager --all 'nvidia*' 'fabric*' 2>&1 || true
echo
echo "=== active units ==="
systemctl list-units --no-pager --all 'nvidia*' 'fabric*' 2>&1 || true
echo
echo "=== failed units ==="
systemctl --failed --no-pager 2>&1 | grep -iE 'nvidia|fabric' || echo "no failed nvidia/fabric units"
`}},
{name: "system/fabric-manager-paths.txt", cmd: []string{"sh", "-c", `
for candidate in \
/usr/bin/nvidia-fabricmanager \
/usr/bin/nv-fabricmanager \
/usr/bin/nvidia-fabricmanagerd \
/usr/bin/nvlsm; do
if [ -e "$candidate" ]; then
echo "=== $candidate ==="
ls -l "$candidate" 2>&1 || true
echo
fi
done
if ! ls /usr/bin/nvidia-fabricmanager /usr/bin/nv-fabricmanager /usr/bin/nvidia-fabricmanagerd /usr/bin/nvlsm >/dev/null 2>&1; then
echo "no fabric manager binaries found"
fi
`}},
{name: "system/lspci-nvidia-bridges-vv.txt", cmd: []string{"sh", "-c", `
if ! command -v lspci >/dev/null 2>&1; then
echo "lspci not found"
@@ -195,6 +234,10 @@ var supportBundleOptionalFiles = []struct {
}{
{name: "system/kern.log", src: "/var/log/kern.log"},
{name: "system/syslog.txt", src: "/var/log/syslog"},
{name: "system/fabricmanager.log", src: "/var/log/fabricmanager.log"},
{name: "system/nvlsm.log", src: "/var/log/nvlsm.log"},
{name: "system/fabricmanager/fabricmanager.log", src: "/var/log/fabricmanager/fabricmanager.log"},
{name: "system/fabricmanager/nvlsm.log", src: "/var/log/fabricmanager/nvlsm.log"},
}
const supportBundleGlob = "????-??-?? (BEE-SP*)*.tar.gz"

File diff suppressed because it is too large Load Diff

View File

@@ -61,6 +61,9 @@ func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult) string {
if result.ScalabilityScore > 0 {
fmt.Fprintf(&b, "**Scalability score:** %.1f%% \n", result.ScalabilityScore)
}
if result.PlatformPowerScore > 0 {
fmt.Fprintf(&b, "**Platform power score:** %.1f%% \n", result.PlatformPowerScore)
}
fmt.Fprintf(&b, "**Overall status:** %s \n", result.OverallStatus)
b.WriteString("\n")
@@ -81,41 +84,92 @@ func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult) string {
b.WriteString("\n")
}
// ── Methodology ───────────────────────────────────────────────────────────
b.WriteString("## Methodology\n\n")
fmt.Fprintf(&b, "- Profile `%s` uses standardized baseline -> warmup -> steady-state -> interconnect 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 (int8, 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 · int8 ×0.25 · 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")
// ── Balanced Scorecard ────────────────────────────────────────────────────
b.WriteString("## Balanced Scorecard\n\n")
// ── Scorecard table ───────────────────────────────────────────────────────
b.WriteString("## Scorecard\n\n")
b.WriteString("| GPU | Status | Composite | Compute | Synthetic | Mixed | Mixed Eff. | TOPS/SM/GHz | Power Sustain | Thermal Sustain | Stability | Interconnect |\n")
b.WriteString("|-----|--------|-----------|---------|-----------|-------|------------|-------------|---------------|-----------------|-----------|-------------|\n")
// Perspective 1: Compatibility — hard stops
b.WriteString("### 1. Compatibility\n\n")
b.WriteString("| GPU | Thermal throttle | Fan duty at throttle | ECC uncorr | Status |\n")
b.WriteString("|-----|------------------|----------------------|------------|--------|\n")
for _, gpu := range result.GPUs {
name := strings.TrimSpace(gpu.Name)
if name == "" {
name = "Unknown GPU"
thermalThrottle := "-"
if gpu.Scores.ThermalThrottlePct > 0 {
thermalThrottle = fmt.Sprintf("%.1f%%", gpu.Scores.ThermalThrottlePct)
}
interconnect := "-"
if gpu.Scores.InterconnectScore > 0 {
interconnect = fmt.Sprintf("%.1f", gpu.Scores.InterconnectScore)
fanAtThrottle := "-"
if result.Cooling != nil && result.Cooling.FanDutyCycleAvailable && gpu.Scores.ThermalThrottlePct > 0 {
fanAtThrottle = fmt.Sprintf("%.0f%%", result.Cooling.P95FanDutyCyclePct)
}
topsPerSM := "-"
if gpu.Scores.TOPSPerSMPerGHz > 0 {
topsPerSM = fmt.Sprintf("%.3f", gpu.Scores.TOPSPerSMPerGHz)
ecc := "-"
if gpu.ECC.Uncorrected > 0 {
ecc = fmt.Sprintf("⛔ %d", gpu.ECC.Uncorrected)
}
compatStatus := "✓ OK"
if gpu.ECC.Uncorrected > 0 || (gpu.Scores.ThermalThrottlePct > 0 && result.Cooling != nil && result.Cooling.FanDutyCycleAvailable && result.Cooling.P95FanDutyCyclePct < 95) {
compatStatus = "⛔ HARD STOP"
}
fmt.Fprintf(&b, "| GPU %d | %s | %s | %s | %s |\n",
gpu.Index, thermalThrottle, fanAtThrottle, ecc, compatStatus)
}
b.WriteString("\n")
// Perspective 2: Thermal headroom
b.WriteString("### 2. Thermal Headroom\n\n")
b.WriteString("| GPU | p95 temp | Slowdown limit | Shutdown limit | Headroom | Thermal throttle | Status |\n")
b.WriteString("|-----|----------|----------------|----------------|----------|------------------|--------|\n")
for _, gpu := range result.GPUs {
shutdownTemp := gpu.ShutdownTempC
if shutdownTemp <= 0 {
shutdownTemp = 90
}
slowdownTemp := gpu.SlowdownTempC
if slowdownTemp <= 0 {
slowdownTemp = 80
}
headroom := gpu.Scores.TempHeadroomC
thermalStatus := "✓ OK"
switch {
case headroom < 10:
thermalStatus = "⛔ CRITICAL"
case gpu.Steady.P95TempC >= slowdownTemp:
thermalStatus = "⚠ WARNING"
}
throttlePct := "-"
if gpu.Scores.ThermalThrottlePct > 0 {
throttlePct = fmt.Sprintf("%.1f%%", gpu.Scores.ThermalThrottlePct)
}
fmt.Fprintf(&b, "| GPU %d | %.1f°C | %.0f°C | %.0f°C | %.1f°C | %s | %s |\n",
gpu.Index, gpu.Steady.P95TempC, slowdownTemp, shutdownTemp, headroom, throttlePct, thermalStatus)
}
b.WriteString("\n")
// Perspective 3: Power delivery
b.WriteString("### 3. Power Delivery\n\n")
b.WriteString("| GPU | Power cap throttle | Power stability | Fan duty (p95) | Status |\n")
b.WriteString("|-----|-------------------|-----------------|----------------|--------|\n")
for _, gpu := range result.GPUs {
powerCap := "-"
if gpu.Scores.PowerCapThrottlePct > 0 {
powerCap = fmt.Sprintf("%.1f%%", gpu.Scores.PowerCapThrottlePct)
}
fanDuty := "-"
if result.Cooling != nil && result.Cooling.FanDutyCycleAvailable {
fanDuty = fmt.Sprintf("%.0f%%", result.Cooling.P95FanDutyCyclePct)
}
powerStatus := "✓ OK"
if gpu.Scores.PowerCapThrottlePct > 5 {
powerStatus = "⚠ POWER LIMITED"
}
fmt.Fprintf(&b, "| GPU %d | %s | %.1f | %s | %s |\n",
gpu.Index, powerCap, gpu.Scores.PowerSustainScore, fanDuty, powerStatus)
}
b.WriteString("\n")
// Perspective 4: Performance
b.WriteString("### 4. Performance\n\n")
b.WriteString("| GPU | Compute TOPS | Synthetic | Mixed | Mixed Eff. | TOPS/SM/GHz |\n")
b.WriteString("|-----|--------------|-----------|-------|------------|-------------|\n")
for _, gpu := range result.GPUs {
synthetic := "-"
if gpu.Scores.SyntheticScore > 0 {
synthetic = fmt.Sprintf("%.2f", gpu.Scores.SyntheticScore)
@@ -128,20 +182,41 @@ func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult) string {
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,
gpu.Scores.StabilityScore,
interconnect,
)
topsPerSM := "-"
if gpu.Scores.TOPSPerSMPerGHz > 0 {
topsPerSM = fmt.Sprintf("%.3f", gpu.Scores.TOPSPerSMPerGHz)
}
fmt.Fprintf(&b, "| GPU %d | **%.2f** | %s | %s | %s | %s |\n",
gpu.Index, gpu.Scores.CompositeScore, synthetic, mixed, mixedEff, topsPerSM)
}
if len(result.PerformanceRampSteps) > 0 {
fmt.Fprintf(&b, "\n**Platform power score (scalability):** %.1f%%\n", result.PlatformPowerScore)
}
b.WriteString("\n")
// Perspective 5: Anomaly flags
b.WriteString("### 5. Anomalies\n\n")
b.WriteString("| GPU | ECC corrected | Sync boost throttle | Power instability | Thermal instability |\n")
b.WriteString("|-----|---------------|---------------------|-------------------|---------------------|\n")
for _, gpu := range result.GPUs {
eccCorr := "-"
if gpu.ECC.Corrected > 0 {
eccCorr = fmt.Sprintf("⚠ %d", gpu.ECC.Corrected)
}
syncBoost := "-"
if gpu.Scores.SyncBoostThrottlePct > 0 {
syncBoost = fmt.Sprintf("%.1f%%", gpu.Scores.SyncBoostThrottlePct)
}
powerVar := "OK"
if gpu.Scores.PowerSustainScore < 70 {
powerVar = "⚠ unstable"
}
thermalVar := "OK"
if gpu.Scores.ThermalSustainScore < 70 {
thermalVar = "⚠ unstable"
}
fmt.Fprintf(&b, "| GPU %d | %s | %s | %s | %s |\n",
gpu.Index, eccCorr, syncBoost, powerVar, thermalVar)
}
b.WriteString("\n")
@@ -171,13 +246,13 @@ func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult) string {
fmt.Fprintf(&b, "- **Power limit:** %.0f W (default %.0f W)\n", gpu.PowerLimitW, gpu.DefaultPowerLimitW)
}
if gpu.PowerLimitDerated {
fmt.Fprintf(&b, "- **Power limit derating:** active after %d targeted_power attempt(s)\n", gpu.PowerCalibrationTries)
fmt.Fprintf(&b, "- **Power limit derating:** active (reduced limit %.0f W)\n", gpu.PowerLimitW)
}
if gpu.CalibratedPeakPowerW > 0 {
if gpu.CalibratedPeakTempC > 0 {
fmt.Fprintf(&b, "- **Power calibration (`dcgmi targeted_power`):** %.0f W p95 at %.1f °C p95\n", gpu.CalibratedPeakPowerW, gpu.CalibratedPeakTempC)
fmt.Fprintf(&b, "- **Calibrated peak power:** %.0f W p95 at %.1f °C p95\n", gpu.CalibratedPeakPowerW, gpu.CalibratedPeakTempC)
} else {
fmt.Fprintf(&b, "- **Power calibration (`dcgmi targeted_power`):** %.0f W p95\n", gpu.CalibratedPeakPowerW)
fmt.Fprintf(&b, "- **Calibrated peak power:** %.0f W p95\n", gpu.CalibratedPeakPowerW)
}
}
if gpu.LockedGraphicsClockMHz > 0 {
@@ -186,14 +261,18 @@ func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult) string {
b.WriteString("\n")
// Steady-state telemetry
fmt.Fprintf(&b, "**Steady-state telemetry** (%ds):\n\n", int(gpu.Steady.DurationSec))
b.WriteString("| | Avg | P95 |\n|---|---|---|\n")
fmt.Fprintf(&b, "| Power | %.1f W | %.1f W |\n", gpu.Steady.AvgPowerW, gpu.Steady.P95PowerW)
fmt.Fprintf(&b, "| Temperature | %.1f °C | %.1f °C |\n", gpu.Steady.AvgTempC, gpu.Steady.P95TempC)
fmt.Fprintf(&b, "| GPU clock | %.0f MHz | %.0f MHz |\n", gpu.Steady.AvgGraphicsClockMHz, gpu.Steady.P95GraphicsClockMHz)
fmt.Fprintf(&b, "| Memory clock | %.0f MHz | %.0f MHz |\n", gpu.Steady.AvgMemoryClockMHz, gpu.Steady.P95MemoryClockMHz)
fmt.Fprintf(&b, "| GPU utilisation | %.1f %% | — |\n", gpu.Steady.AvgUsagePct)
b.WriteString("\n")
if benchmarkTelemetryAvailable(gpu.Steady) {
fmt.Fprintf(&b, "**Steady-state telemetry** (%ds):\n\n", int(gpu.Steady.DurationSec))
b.WriteString("| | Avg | P95 |\n|---|---|---|\n")
fmt.Fprintf(&b, "| Power | %.1f W | %.1f W |\n", gpu.Steady.AvgPowerW, gpu.Steady.P95PowerW)
fmt.Fprintf(&b, "| Temperature | %.1f °C | %.1f °C |\n", gpu.Steady.AvgTempC, gpu.Steady.P95TempC)
fmt.Fprintf(&b, "| GPU clock | %.0f MHz | %.0f MHz |\n", gpu.Steady.AvgGraphicsClockMHz, gpu.Steady.P95GraphicsClockMHz)
fmt.Fprintf(&b, "| Memory clock | %.0f MHz | %.0f MHz |\n", gpu.Steady.AvgMemoryClockMHz, gpu.Steady.P95MemoryClockMHz)
fmt.Fprintf(&b, "| GPU utilisation | %.1f %% | — |\n", gpu.Steady.AvgUsagePct)
b.WriteString("\n")
} else {
b.WriteString("**Steady-state telemetry:** unavailable\n\n")
}
// Per-precision stability phases.
if len(gpu.PrecisionSteady) > 0 {
@@ -329,6 +408,19 @@ func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult) string {
}
}
// ── Platform Scalability ──────────────────────────────────────────────────
if len(result.PerformanceRampSteps) > 0 {
b.WriteString("## Platform Scalability (Performance Ramp)\n\n")
fmt.Fprintf(&b, "**Platform power score:** %.1f%% \n\n", result.PlatformPowerScore)
b.WriteString("| k GPUs | GPU Indices | Total Synthetic TOPS | Scalability |\n")
b.WriteString("|--------|-------------|----------------------|-------------|\n")
for _, step := range result.PerformanceRampSteps {
fmt.Fprintf(&b, "| %d | %s | %.2f | %.1f%% |\n",
step.StepIndex, joinIndexList(step.GPUIndices), step.TotalSyntheticTOPS, step.ScalabilityPct)
}
b.WriteString("\n")
}
// ── Raw files ─────────────────────────────────────────────────────────────
b.WriteString("## Raw Files\n\n")
b.WriteString("- `result.json`\n- `report.md`\n- `summary.txt`\n- `verbose.log`\n")

View File

@@ -49,8 +49,8 @@ func TestBuildBenchmarkSteadyPlanStandard(t *testing.T) {
benchmarkPrecisionPhases,
func(label string) string { return label },
)
if len(labels) != 7 || len(phases) != 7 {
t.Fatalf("labels=%d phases=%d want 7", len(labels), len(phases))
if len(labels) != 5 || len(phases) != 5 {
t.Fatalf("labels=%d phases=%d want 5", len(labels), len(phases))
}
if basePhaseSec != 60 {
t.Fatalf("basePhaseSec=%d want 60", basePhaseSec)
@@ -61,7 +61,7 @@ func TestBuildBenchmarkSteadyPlanStandard(t *testing.T) {
if phases[len(phases)-1].PlanLabel != "mixed" || phases[len(phases)-1].DurationSec != 300 {
t.Fatalf("mixed phase=%+v want duration 300", phases[len(phases)-1])
}
if benchmarkPlanDurationsCSV(phases) != "60,60,60,60,60,60,300" {
if benchmarkPlanDurationsCSV(phases) != "60,60,60,60,300" {
t.Fatalf("durations=%q", benchmarkPlanDurationsCSV(phases))
}
}
@@ -80,7 +80,7 @@ func TestBuildBenchmarkSteadyPlanStability(t *testing.T) {
if mixedPhaseSec != 3600 {
t.Fatalf("mixedPhaseSec=%d want 3600", mixedPhaseSec)
}
if benchmarkPlanDurationsCSV(phases) != "300,300,300,300,300,300,3600" {
if benchmarkPlanDurationsCSV(phases) != "300,300,300,300,3600" {
t.Fatalf("durations=%q", benchmarkPlanDurationsCSV(phases))
}
}
@@ -99,7 +99,7 @@ func TestBuildBenchmarkSteadyPlanOvernight(t *testing.T) {
if mixedPhaseSec != 14400 {
t.Fatalf("mixedPhaseSec=%d want 14400", mixedPhaseSec)
}
if benchmarkPlanDurationsCSV(phases) != "3600,3600,3600,3600,3600,3600,14400" {
if benchmarkPlanDurationsCSV(phases) != "3600,3600,3600,3600,14400" {
t.Fatalf("durations=%q", benchmarkPlanDurationsCSV(phases))
}
}
@@ -133,10 +133,10 @@ func TestSplitBenchmarkRowsByPlannedPhaseUsesPhaseDurations(t *testing.T) {
func TestBenchmarkSupportedPrecisionsSkipsFP4BeforeBlackwell(t *testing.T) {
t.Parallel()
if got := benchmarkSupportedPrecisions("9.0"); strings.Join(got, ",") != "int8,fp8,fp16,fp32,fp64" {
if got := benchmarkSupportedPrecisions("9.0"); strings.Join(got, ",") != "int8,fp8,fp16,fp32" {
t.Fatalf("supported=%v", got)
}
if got := benchmarkSupportedPrecisions("10.0"); strings.Join(got, ",") != "int8,fp8,fp16,fp32,fp64,fp4" {
if got := benchmarkSupportedPrecisions("10.0"); strings.Join(got, ",") != "int8,fp8,fp16,fp32" {
t.Fatalf("supported=%v", got)
}
}
@@ -314,6 +314,30 @@ func TestRenderBenchmarkReportListsUnifiedArtifacts(t *testing.T) {
}
}
func TestScoreBenchmarkGPUIgnoresDisabledPrecisions(t *testing.T) {
t.Parallel()
score := scoreBenchmarkGPUResult(BenchmarkGPUResult{
PrecisionSteady: []BenchmarkPrecisionSteadyPhase{
{Precision: "fp16", WeightedTeraOpsPerSec: 100},
{Precision: "fp64", WeightedTeraOpsPerSec: 999},
{Precision: "fp4", WeightedTeraOpsPerSec: 999},
},
PrecisionResults: []BenchmarkPrecisionResult{
{Category: "fp32_tf32", Supported: true, WeightedTeraOpsPerSec: 50},
{Category: "fp64", Supported: true, WeightedTeraOpsPerSec: 999},
{Category: "fp4", Supported: true, WeightedTeraOpsPerSec: 999},
},
})
if score.SyntheticScore != 100 {
t.Fatalf("SyntheticScore=%f want 100", score.SyntheticScore)
}
if score.MixedScore != 50 {
t.Fatalf("MixedScore=%f want 50", score.MixedScore)
}
}
func TestEnrichGPUInfoWithMaxClocks(t *testing.T) {
t.Parallel()

View File

@@ -31,6 +31,7 @@ type BenchmarkCoolingSummary struct {
Available bool `json:"available"`
AvgFanRPM float64 `json:"avg_fan_rpm,omitempty"`
FanDutyCycleAvailable bool `json:"fan_duty_cycle_available,omitempty"`
FanDutyCycleEstimated bool `json:"fan_duty_cycle_estimated,omitempty"`
AvgFanDutyCyclePct float64 `json:"avg_fan_duty_cycle_pct,omitempty"`
P95FanDutyCyclePct float64 `json:"p95_fan_duty_cycle_pct,omitempty"`
Notes []string `json:"notes,omitempty"`
@@ -55,27 +56,32 @@ type NvidiaBenchmarkOptions struct {
}
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"`
RampStep int `json:"ramp_step,omitempty"`
RampTotal int `json:"ramp_total,omitempty"`
RampRunID string `json:"ramp_run_id,omitempty"`
ScalabilityScore float64 `json:"scalability_score,omitempty"`
OverallStatus string `json:"overall_status"`
SelectedGPUIndices []int `json:"selected_gpu_indices"`
Findings []string `json:"findings,omitempty"`
Warnings []string `json:"warnings,omitempty"`
Normalization BenchmarkNormalization `json:"normalization"`
HostConfig *BenchmarkHostConfig `json:"host_config,omitempty"`
CPULoad *BenchmarkCPULoad `json:"cpu_load,omitempty"`
Cooling *BenchmarkCoolingSummary `json:"cooling,omitempty"`
GPUs []BenchmarkGPUResult `json:"gpus"`
Interconnect *BenchmarkInterconnectResult `json:"interconnect,omitempty"`
ServerPower *BenchmarkServerPower `json:"server_power,omitempty"`
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"`
RampStep int `json:"ramp_step,omitempty"`
RampTotal int `json:"ramp_total,omitempty"`
RampRunID string `json:"ramp_run_id,omitempty"`
ScalabilityScore float64 `json:"scalability_score,omitempty"`
// PlatformPowerScore is the mean compute scalability across ramp steps 2..N.
// 100% = each added GPU contributes exactly its single-card throughput.
// < 100% = throughput loss due to thermal throttle, power limits, or contention.
PlatformPowerScore float64 `json:"platform_power_score,omitempty"`
PerformanceRampSteps []NvidiaPerformanceRampStep `json:"performance_ramp_steps,omitempty"`
OverallStatus string `json:"overall_status"`
SelectedGPUIndices []int `json:"selected_gpu_indices"`
Findings []string `json:"findings,omitempty"`
Warnings []string `json:"warnings,omitempty"`
Normalization BenchmarkNormalization `json:"normalization"`
HostConfig *BenchmarkHostConfig `json:"host_config,omitempty"`
CPULoad *BenchmarkCPULoad `json:"cpu_load,omitempty"`
Cooling *BenchmarkCoolingSummary `json:"cooling,omitempty"`
GPUs []BenchmarkGPUResult `json:"gpus"`
Interconnect *BenchmarkInterconnectResult `json:"interconnect,omitempty"`
ServerPower *BenchmarkServerPower `json:"server_power,omitempty"`
}
type BenchmarkNormalization struct {
@@ -107,6 +113,12 @@ type BenchmarkGPUResult struct {
PowerLimitDerated bool `json:"power_limit_derated,omitempty"`
MultiprocessorCount int `json:"multiprocessor_count,omitempty"`
DefaultPowerLimitW float64 `json:"default_power_limit_w,omitempty"`
// ShutdownTempC is the hardware thermal shutdown threshold for this GPU,
// sourced from nvidia-smi -q ("GPU Shutdown Temp"). Fallback: 90°C.
ShutdownTempC float64 `json:"shutdown_temp_c,omitempty"`
// SlowdownTempC is the software throttle onset threshold ("GPU Slowdown Temp").
// Fallback: 80°C.
SlowdownTempC float64 `json:"slowdown_temp_c,omitempty"`
// CalibratedPeakPowerW is the p95 power measured during a short
// dcgmi targeted_power calibration run before the main benchmark.
// Used as the reference denominator for PowerSustainScore instead of
@@ -206,9 +218,30 @@ type BenchmarkScorecard struct {
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"`
// StabilityScore: fraction of steady-state time the GPU spent throttling
// (thermal + power cap combined). 0% throttle = 100; 100% throttle = 0.
StabilityScore float64 `json:"stability_score"`
// Throttle breakdown — percentage of steady-state time in each throttle type.
// Used for diagnosis: tells WHY the GPU throttled, not just whether it did.
ThermalThrottlePct float64 `json:"thermal_throttle_pct"` // HW+SW thermal slowdown
PowerCapThrottlePct float64 `json:"power_cap_throttle_pct"` // SW power cap
SyncBoostThrottlePct float64 `json:"sync_boost_throttle_pct,omitempty"`
// Temperature headroom: distance to the 100°C destruction threshold.
// TempHeadroomC = 100 - P95TempC. < 20°C = warning; < 10°C = critical.
// Independent of throttle — a GPU at 86°C without throttle is still in the red zone.
TempHeadroomC float64 `json:"temp_headroom_c"`
InterconnectScore float64 `json:"interconnect_score"`
// ServerQualityScore (0100) reflects server infrastructure quality independent
// of GPU model. Combines throttle time, power variance, and temp variance.
// Use this to compare servers with the same GPU, or to flag a bad server
// that throttles an otherwise fast GPU.
ServerQualityScore float64 `json:"server_quality_score"`
// CompositeScore is the raw compute score (TOPS, fp32-equivalent).
// A throttling GPU will score lower here automatically — no quality multiplier.
CompositeScore float64 `json:"composite_score"`
// TOPSPerSMPerGHz is compute efficiency independent of clock speed and SM count.
TOPSPerSMPerGHz float64 `json:"tops_per_sm_per_ghz,omitempty"`
}
@@ -265,16 +298,31 @@ type NvidiaPowerBenchResult struct {
RecommendedSlotOrder []int `json:"recommended_slot_order,omitempty"`
RampSteps []NvidiaPowerBenchStep `json:"ramp_steps,omitempty"`
OverallStatus string `json:"overall_status"`
Findings []string `json:"findings,omitempty"`
GPUs []NvidiaPowerBenchGPU `json:"gpus"`
// PlatformMaxTDPW is the sum of per-GPU stable power limits found during the
// cumulative thermal ramp. Represents the actual sustained power budget of
// this server under full GPU load. Use for rack power planning.
PlatformMaxTDPW float64 `json:"platform_max_tdp_w"`
// ServerPower captures IPMI server power delta (idle→loaded) measured in
// parallel with the thermal ramp. Use to compare GPU-reported TDP against
// actual wall-power draw as seen by the server's power supply.
ServerPower *BenchmarkServerPower `json:"server_power,omitempty"`
Findings []string `json:"findings,omitempty"`
GPUs []NvidiaPowerBenchGPU `json:"gpus"`
}
type NvidiaPowerBenchGPU struct {
Index int `json:"index"`
Name string `json:"name,omitempty"`
BusID string `json:"bus_id,omitempty"`
DefaultPowerLimitW float64 `json:"default_power_limit_w,omitempty"`
AppliedPowerLimitW float64 `json:"applied_power_limit_w,omitempty"`
Index int `json:"index"`
Name string `json:"name,omitempty"`
BusID string `json:"bus_id,omitempty"`
DefaultPowerLimitW float64 `json:"default_power_limit_w,omitempty"`
// AppliedPowerLimitW is the stable limit found during single-card calibration.
AppliedPowerLimitW float64 `json:"applied_power_limit_w,omitempty"`
// StablePowerLimitW is the final fixed limit for this GPU after the
// cumulative thermal ramp. This is the limit at which the GPU operated
// stably with all other GPUs running simultaneously at their own limits.
// May be lower than AppliedPowerLimitW if multi-GPU thermal load required
// additional derating.
StablePowerLimitW float64 `json:"stable_power_limit_w,omitempty"`
MaxObservedPowerW float64 `json:"max_observed_power_w,omitempty"`
MaxObservedTempC float64 `json:"max_observed_temp_c,omitempty"`
CalibrationAttempts int `json:"calibration_attempts,omitempty"`
@@ -283,16 +331,45 @@ type NvidiaPowerBenchGPU struct {
Notes []string `json:"notes,omitempty"`
// CoolingWarning mirrors BenchmarkGPUResult.CoolingWarning for the power workflow.
CoolingWarning string `json:"cooling_warning,omitempty"`
// ServerLoadedW is the IPMI server power reading captured during this
// GPU's single-card calibration run. ServerDeltaW = ServerLoadedW idle.
ServerLoadedW float64 `json:"server_loaded_w,omitempty"`
ServerDeltaW float64 `json:"server_delta_w,omitempty"`
// Telemetry holds the aggregated stats from the final converged calibration
// attempt for this GPU (temperature, power, fan, clock percentiles).
Telemetry *BenchmarkTelemetrySummary `json:"telemetry,omitempty"`
}
type NvidiaPowerBenchStep struct {
StepIndex int `json:"step_index"`
GPUIndices []int `json:"gpu_indices"`
TotalObservedPowerW float64 `json:"total_observed_power_w,omitempty"`
AvgObservedPowerW float64 `json:"avg_observed_power_w,omitempty"`
MinPowerRealizationPct float64 `json:"min_power_realization_pct,omitempty"`
AvgPowerRealizationPct float64 `json:"avg_power_realization_pct,omitempty"`
DeratedGPUCount int `json:"derated_gpu_count,omitempty"`
Status string `json:"status"`
Notes []string `json:"notes,omitempty"`
StepIndex int `json:"step_index"`
GPUIndices []int `json:"gpu_indices"`
// NewGPUIndex is the GPU whose stable limit was searched in this step.
NewGPUIndex int `json:"new_gpu_index"`
// NewGPUStableLimitW is the stable power limit found for the new GPU.
NewGPUStableLimitW float64 `json:"new_gpu_stable_limit_w,omitempty"`
TotalObservedPowerW float64 `json:"total_observed_power_w,omitempty"`
AvgObservedPowerW float64 `json:"avg_observed_power_w,omitempty"`
Derated bool `json:"derated,omitempty"`
Status string `json:"status"`
Notes []string `json:"notes,omitempty"`
// ServerLoadedW is the IPMI server power reading captured during this
// ramp step's calibration run. ServerDeltaW = ServerLoadedW idle.
ServerLoadedW float64 `json:"server_loaded_w,omitempty"`
ServerDeltaW float64 `json:"server_delta_w,omitempty"`
}
// NvidiaPerformanceRampStep holds per-step performance data for the
// scalability ramp-up phase of the performance benchmark.
type NvidiaPerformanceRampStep struct {
StepIndex int `json:"step_index"`
GPUIndices []int `json:"gpu_indices"`
// TotalSyntheticTOPS is the sum of per-GPU SyntheticScore (fp32-equivalent
// TOPS from dedicated single-precision phases) across all GPUs in this step.
TotalSyntheticTOPS float64 `json:"total_synthetic_tops"`
TotalMixedTOPS float64 `json:"total_mixed_tops,omitempty"`
// ScalabilityPct = TotalSyntheticTOPS / (k × best_single_gpu_tops) × 100.
// 100% = perfect linear scaling. < 100% = thermal/power/interconnect loss.
ScalabilityPct float64 `json:"scalability_pct"`
Status string `json:"status"`
Notes []string `json:"notes,omitempty"`
}

View File

@@ -27,6 +27,7 @@ type GPUMetricRow struct {
FanAvgRPM float64 `json:"fan_avg_rpm,omitempty"`
FanDutyCyclePct float64 `json:"fan_duty_cycle_pct,omitempty"`
FanDutyCycleAvailable bool `json:"fan_duty_cycle_available,omitempty"`
FanDutyCycleEstimated bool `json:"fan_duty_cycle_estimated,omitempty"`
}
// sampleGPUMetrics runs nvidia-smi once and returns current metrics for each GPU.
@@ -147,14 +148,18 @@ 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("stage,elapsed_sec,gpu_index,temperature_c,usage_pct,mem_usage_pct,power_w,clock_mhz,mem_clock_mhz,fan_avg_rpm,fan_duty_cycle_pct,fan_duty_cycle_available\n")
b.WriteString("stage,elapsed_sec,gpu_index,temperature_c,usage_pct,mem_usage_pct,power_w,clock_mhz,mem_clock_mhz,fan_avg_rpm,fan_duty_cycle_pct,fan_duty_cycle_available,fan_duty_cycle_estimated\n")
for _, r := range rows {
dutyAvail := 0
if r.FanDutyCycleAvailable {
dutyAvail = 1
}
fmt.Fprintf(&b, "%s,%.1f,%d,%.1f,%.1f,%.1f,%.1f,%.0f,%.0f,%.0f,%.1f,%d\n",
strconv.Quote(strings.TrimSpace(r.Stage)), r.ElapsedSec, r.GPUIndex, r.TempC, r.UsagePct, r.MemUsagePct, r.PowerW, r.ClockMHz, r.MemClockMHz, r.FanAvgRPM, r.FanDutyCyclePct, dutyAvail)
dutyEstimated := 0
if r.FanDutyCycleEstimated {
dutyEstimated = 1
}
fmt.Fprintf(&b, "%s,%.1f,%d,%.1f,%.1f,%.1f,%.1f,%.0f,%.0f,%.0f,%.1f,%d,%d\n",
strconv.Quote(strings.TrimSpace(r.Stage)), r.ElapsedSec, r.GPUIndex, r.TempC, r.UsagePct, r.MemUsagePct, r.PowerW, r.ClockMHz, r.MemClockMHz, r.FanAvgRPM, r.FanDutyCyclePct, dutyAvail, dutyEstimated)
}
return os.WriteFile(path, b.Bytes(), 0644)
}

View File

@@ -28,6 +28,8 @@ var runtimeTrackedServices = []string{
"bee-audit",
"bee-web",
"bee-sshsetup",
"nvidia-dcgm",
"nvidia-fabricmanager",
}
func (s *System) CollectRuntimeHealth(exportDir string) (schema.RuntimeHealth, error) {

View File

@@ -366,12 +366,14 @@ func (s *System) ResetNvidiaGPU(index int) (string, error) {
return string(raw), err
}
// RunNCCLTests runs nccl-tests all_reduce_perf across all NVIDIA GPUs.
// RunNCCLTests runs nccl-tests all_reduce_perf across the selected NVIDIA GPUs.
// Measures collective communication bandwidth over NVLink/PCIe.
func (s *System) RunNCCLTests(ctx context.Context, baseDir string, logFunc func(string)) (string, error) {
// detect GPU count
out, _ := exec.Command("nvidia-smi", "--query-gpu=index", "--format=csv,noheader").Output()
gpuCount := len(strings.Split(strings.TrimSpace(string(out)), "\n"))
func (s *System) RunNCCLTests(ctx context.Context, baseDir string, gpuIndices []int, logFunc func(string)) (string, error) {
selected, err := resolveDCGMGPUIndices(gpuIndices)
if err != nil {
return "", err
}
gpuCount := len(selected)
if gpuCount < 1 {
gpuCount = 1
}
@@ -380,7 +382,7 @@ func (s *System) RunNCCLTests(ctx context.Context, baseDir string, logFunc func(
satJob{name: "02-all-reduce-perf.log", cmd: []string{
"all_reduce_perf", "-b", "512M", "-e", "4G", "-f", "2",
"-g", strconv.Itoa(gpuCount), "--iters", "20",
}},
}, env: nvidiaVisibleDevicesEnv(selected)},
), logFunc)
}
@@ -426,6 +428,13 @@ func (s *System) RunNvidiaTargetedPowerPack(ctx context.Context, baseDir string,
if err != nil {
return "", err
}
// Kill any lingering nvvs/dcgmi processes from a previous interrupted run
// before starting — otherwise dcgmi diag fails with DCGM_ST_IN_USE (-34).
if killed := KillTestWorkers(); len(killed) > 0 && logFunc != nil {
for _, p := range killed {
logFunc(fmt.Sprintf("pre-flight: killed stale worker pid=%d name=%s", p.PID, p.Name))
}
}
return runAcceptancePackCtx(ctx, baseDir, "gpu-nvidia-targeted-power", withNvidiaPersistenceMode(
satJob{name: "01-nvidia-smi-q.log", cmd: []string{"nvidia-smi", "-q"}},
satJob{
@@ -443,6 +452,13 @@ func (s *System) RunNvidiaPulseTestPack(ctx context.Context, baseDir string, dur
if err != nil {
return "", err
}
// Kill any lingering nvvs/dcgmi processes from a previous interrupted run
// before starting — otherwise dcgmi diag fails with DCGM_ST_IN_USE (-34).
if killed := KillTestWorkers(); len(killed) > 0 && logFunc != nil {
for _, p := range killed {
logFunc(fmt.Sprintf("pre-flight: killed stale worker pid=%d name=%s", p.PID, p.Name))
}
}
return runAcceptancePackCtx(ctx, baseDir, "gpu-nvidia-pulse", withNvidiaPersistenceMode(
satJob{name: "01-nvidia-smi-q.log", cmd: []string{"nvidia-smi", "-q"}},
satJob{
@@ -460,6 +476,13 @@ func (s *System) RunNvidiaBandwidthPack(ctx context.Context, baseDir string, gpu
if err != nil {
return "", err
}
// Kill any lingering nvvs/dcgmi processes from a previous interrupted run
// before starting — otherwise dcgmi diag fails with DCGM_ST_IN_USE (-34).
if killed := KillTestWorkers(); len(killed) > 0 && logFunc != nil {
for _, p := range killed {
logFunc(fmt.Sprintf("pre-flight: killed stale worker pid=%d name=%s", p.PID, p.Name))
}
}
return runAcceptancePackCtx(ctx, baseDir, "gpu-nvidia-bandwidth", withNvidiaPersistenceMode(
satJob{name: "01-nvidia-smi-q.log", cmd: []string{"nvidia-smi", "-q"}},
satJob{
@@ -552,10 +575,16 @@ func (s *System) RunMemoryAcceptancePack(ctx context.Context, baseDir string, si
if passes <= 0 {
passes = 1
}
// Bound memtester with a hard wall-clock timeout: ~2.5 min per 100 MB per
// pass, plus a fixed 2-minute buffer. Without this, a stuck memory
// controller can cause memtester to spin forever on a single subtest.
timeoutSec := sizeMB*passes*150/100 + 120
// Keep Validate Memory bounded to a quick diagnostic window. The timeout is
// intentionally conservative enough for healthy systems while avoiding the
// prior 30-80 minute hangs caused by memtester spinning on a bad subtest.
timeoutSec := sizeMB*passes*20/100 + 60
if timeoutSec < 180 {
timeoutSec = 180
}
if timeoutSec > 900 {
timeoutSec = 900
}
return runAcceptancePackCtx(ctx, baseDir, "memory", []satJob{
{name: "01-free-before.log", cmd: []string{"free", "-h"}},
{name: "02-memtester.log", cmd: []string{"timeout", fmt.Sprintf("%d", timeoutSec), "memtester", fmt.Sprintf("%dM", sizeMB), fmt.Sprintf("%d", passes)}},

View File

@@ -4,6 +4,7 @@ import (
"context"
"encoding/json"
"fmt"
"math"
"os"
"os/exec"
"path/filepath"
@@ -56,13 +57,37 @@ type cachedPowerReading struct {
UpdatedAt time.Time
}
type fanObservationState struct {
MaxRPM map[string]float64 `json:"max_rpm"`
}
type fanPeakCandidate struct {
FirstSeen time.Time
RPM float64
}
var (
systemPowerCacheMu sync.Mutex
systemPowerCache cachedPowerReading
fanObservationMu sync.Mutex
fanObservation fanObservationState
fanObservationInit bool
fanPeakCandidates = make(map[string]fanPeakCandidate)
)
const systemPowerHoldTTL = 15 * time.Second
var fanObservationStatePath = "/var/log/bee-sat/fan-observation.json"
const fanObservationMinPeakHold = time.Second
func normalizeObservedFanMaxRPM(rpm float64) float64 {
if rpm <= 0 {
return 0
}
return math.Ceil(rpm/1000.0) * 1000.0
}
// RunFanStressTest runs a two-phase GPU stress test while monitoring fan speeds,
// temperatures, and power draw every second. Exports metrics.csv and fan-sensors.csv.
// Designed to reproduce case-04 fan-speed lag and detect GPU thermal throttling.
@@ -310,11 +335,13 @@ func sampleFanSpeeds() ([]FanReading, error) {
out, err := exec.Command("ipmitool", "sdr", "type", "Fan").Output()
if err == nil {
if fans := parseFanSpeeds(string(out)); len(fans) > 0 {
updateFanObservation(fans, time.Now())
return fans, nil
}
}
fans, sensorsErr := sampleFanSpeedsViaSensorsJSON()
if len(fans) > 0 {
updateFanObservation(fans, time.Now())
return fans, nil
}
if err != nil {
@@ -323,6 +350,119 @@ func sampleFanSpeeds() ([]FanReading, error) {
return nil, sensorsErr
}
func loadFanObservationLocked() {
if fanObservationInit {
return
}
fanObservationInit = true
fanObservation.MaxRPM = make(map[string]float64)
raw, err := os.ReadFile(fanObservationStatePath)
if err != nil || len(raw) == 0 {
return
}
var persisted fanObservationState
if json.Unmarshal(raw, &persisted) != nil {
return
}
for name, rpm := range persisted.MaxRPM {
name = strings.TrimSpace(name)
if name == "" || rpm <= 0 {
continue
}
fanObservation.MaxRPM[name] = rpm
}
}
func saveFanObservationLocked() {
if len(fanObservation.MaxRPM) == 0 {
return
}
dir := filepath.Dir(fanObservationStatePath)
if dir == "" || dir == "." {
dir = "/var/log/bee-sat"
}
if err := os.MkdirAll(dir, 0755); err != nil {
return
}
raw, err := json.MarshalIndent(fanObservation, "", " ")
if err != nil {
return
}
_ = os.WriteFile(fanObservationStatePath, raw, 0644)
}
func updateFanObservation(fans []FanReading, now time.Time) {
if len(fans) == 0 {
return
}
fanObservationMu.Lock()
defer fanObservationMu.Unlock()
loadFanObservationLocked()
changed := false
for _, fan := range fans {
name := strings.TrimSpace(fan.Name)
if name == "" || fan.RPM <= 0 {
continue
}
currentMax := fanObservation.MaxRPM[name]
if fan.RPM <= currentMax {
delete(fanPeakCandidates, name)
continue
}
if cand, ok := fanPeakCandidates[name]; ok {
if now.Sub(cand.FirstSeen) >= fanObservationMinPeakHold {
newMax := math.Max(cand.RPM, fan.RPM)
if newMax > currentMax {
fanObservation.MaxRPM[name] = normalizeObservedFanMaxRPM(newMax)
changed = true
}
delete(fanPeakCandidates, name)
continue
}
if fan.RPM > cand.RPM {
fanPeakCandidates[name] = fanPeakCandidate{FirstSeen: cand.FirstSeen, RPM: fan.RPM}
}
continue
}
fanPeakCandidates[name] = fanPeakCandidate{FirstSeen: now, RPM: fan.RPM}
}
if changed {
saveFanObservationLocked()
}
}
func estimateFanDutyCyclePctFromObservation(fans []FanReading) (float64, bool) {
if len(fans) == 0 {
return 0, false
}
fanObservationMu.Lock()
defer fanObservationMu.Unlock()
loadFanObservationLocked()
var samples []float64
for _, fan := range fans {
name := strings.TrimSpace(fan.Name)
if name == "" || fan.RPM <= 0 {
continue
}
maxRPM := fanObservation.MaxRPM[name]
if maxRPM <= 0 {
continue
}
pct := fan.RPM / maxRPM * 100.0
if pct > 100 {
pct = 100
}
if pct < 0 {
pct = 0
}
samples = append(samples, pct)
}
if len(samples) == 0 {
return 0, false
}
return benchmarkMean(samples), true
}
// parseFanSpeeds parses "ipmitool sdr type Fan" output.
// Handles two formats:
//
@@ -428,12 +568,27 @@ func sampleFanSpeedsViaSensorsJSON() ([]FanReading, error) {
// sampleFanDutyCyclePct reads fan PWM/duty-cycle controls from lm-sensors.
// Returns the average duty cycle across all exposed PWM controls.
func sampleFanDutyCyclePct() (float64, bool) {
func sampleFanDutyCyclePct() (float64, bool, bool) {
out, err := exec.Command("sensors", "-j").Output()
if err != nil || len(out) == 0 {
return 0, false
fans, fanErr := sampleFanSpeeds()
if fanErr != nil {
return 0, false, false
}
return sampleFanDutyCyclePctFromFans(fans)
}
return parseFanDutyCyclePctSensorsJSON(out)
pct, ok := parseFanDutyCyclePctSensorsJSON(out)
return pct, ok, false
}
func sampleFanDutyCyclePctFromFans(fans []FanReading) (float64, bool, bool) {
if len(fans) == 0 {
return 0, false, false
}
if pct, ok := estimateFanDutyCyclePctFromObservation(fans); ok {
return pct, true, true
}
return 0, false, false
}
func parseFanDutyCyclePctSensorsJSON(raw []byte) (float64, bool) {

View File

@@ -1,6 +1,7 @@
package platform
import (
"path/filepath"
"testing"
"time"
)
@@ -50,6 +51,53 @@ func TestParseFanDutyCyclePctSensorsJSON(t *testing.T) {
}
}
func TestEstimateFanDutyCyclePctFromObservation(t *testing.T) {
t.Parallel()
oldPath := fanObservationStatePath
oldState := fanObservation
oldInit := fanObservationInit
oldCandidates := fanPeakCandidates
fanObservationStatePath = filepath.Join(t.TempDir(), "fan-observation.json")
fanObservation = fanObservationState{}
fanObservationInit = false
fanPeakCandidates = make(map[string]fanPeakCandidate)
t.Cleanup(func() {
fanObservationStatePath = oldPath
fanObservation = oldState
fanObservationInit = oldInit
fanPeakCandidates = oldCandidates
})
start := time.Unix(100, 0)
updateFanObservation([]FanReading{{Name: "FAN1", RPM: 5000}}, start)
if _, ok := estimateFanDutyCyclePctFromObservation([]FanReading{{Name: "FAN1", RPM: 2500}}); ok {
t.Fatalf("single-sample spike should not establish observed max")
}
updateFanObservation([]FanReading{{Name: "FAN1", RPM: 5200}}, start.Add(500*time.Millisecond))
updateFanObservation([]FanReading{{Name: "FAN1", RPM: 5100}}, start.Add(1500*time.Millisecond))
got, ok := estimateFanDutyCyclePctFromObservation([]FanReading{{Name: "FAN1", RPM: 2600}})
if !ok {
t.Fatalf("expected estimated duty cycle from persisted observed max")
}
if got < 43 || got > 44 {
t.Fatalf("got=%v want ~43.3", got)
}
fanObservation = fanObservationState{}
fanObservationInit = false
fanPeakCandidates = make(map[string]fanPeakCandidate)
got, ok = estimateFanDutyCyclePctFromObservation([]FanReading{{Name: "FAN1", RPM: 2600}})
if !ok {
t.Fatalf("expected persisted observed max to be reloaded from disk")
}
if got < 43 || got > 44 {
t.Fatalf("reloaded got=%v want ~43.3", got)
}
}
func TestParseDCMIPowerReading(t *testing.T) {
raw := `
Instantaneous power reading: 512 Watts

View File

@@ -321,6 +321,19 @@ func TestNvidiaDCGMNamedDiagCommandUsesDurationAndSelection(t *testing.T) {
}
}
func TestNvidiaDCGMNamedDiagCommandSkipsDurationForNVBandwidth(t *testing.T) {
cmd := nvidiaDCGMNamedDiagCommand("nvbandwidth", 0, []int{2, 0})
want := []string{"dcgmi", "diag", "-r", "nvbandwidth", "-i", "2,0"}
if len(cmd) != len(want) {
t.Fatalf("cmd len=%d want %d (%v)", len(cmd), len(want), cmd)
}
for i := range want {
if cmd[i] != want[i] {
t.Fatalf("cmd[%d]=%q want %q", i, cmd[i], want[i])
}
}
}
func TestNvidiaVisibleDevicesEnvUsesSelectedGPUs(t *testing.T) {
env := nvidiaVisibleDevicesEnv([]int{0, 2, 4})
if len(env) != 2 {

View File

@@ -628,8 +628,10 @@ func (h *handler) handleAPIBenchmarkNvidiaRunKind(target string) http.HandlerFun
}
if rampUp && len(body.GPUIndices) > 1 {
// Ramp-up mode: resolve GPU list, then create one task per prefix
// [gpu0], [gpu0,gpu1], ..., [gpu0,...,gpuN-1], each running in parallel.
// Ramp-up mode: RunNvidiaPowerBench internally ramps from 1 to N GPUs
// in Phase 2 (one additional GPU per step). A single task with all
// selected GPUs is sufficient — spawning N tasks with growing subsets
// would repeat all earlier steps redundantly.
gpus, err := apiListNvidiaGPUs(h.opts.App)
if err != nil {
writeError(w, http.StatusBadRequest, err.Error())
@@ -646,35 +648,27 @@ func (h *handler) handleAPIBenchmarkNvidiaRunKind(target string) http.HandlerFun
} else {
now := time.Now()
rampRunID := fmt.Sprintf("ramp-%s", now.UTC().Format("20060102-150405"))
var allTasks []*Task
for step := 1; step <= len(resolved); step++ {
subset := resolved[:step]
stepName := fmt.Sprintf("%s · ramp %d/%d · GPU %s", name, step, len(resolved), formatGPUIndexList(subset))
t := &Task{
ID: newJobID("bee-bench-nvidia"),
Name: stepName,
Target: target,
Priority: defaultTaskPriority(target, taskParams{}),
Status: TaskPending,
CreatedAt: now,
params: taskParams{
GPUIndices: append([]int(nil), subset...),
SizeMB: body.SizeMB,
BenchmarkProfile: body.Profile,
RunNCCL: runNCCL && step == len(resolved),
ParallelGPUs: true,
RampStep: step,
RampTotal: len(resolved),
RampRunID: rampRunID,
DisplayName: stepName,
},
}
allTasks = append(allTasks, t)
taskName := fmt.Sprintf("%s · ramp 1%d · GPU %s", name, len(resolved), formatGPUIndexList(resolved))
t := &Task{
ID: newJobID("bee-bench-nvidia"),
Name: taskName,
Target: target,
Priority: defaultTaskPriority(target, taskParams{}),
Status: TaskPending,
CreatedAt: now,
params: taskParams{
GPUIndices: append([]int(nil), resolved...),
SizeMB: body.SizeMB,
BenchmarkProfile: body.Profile,
RunNCCL: runNCCL,
ParallelGPUs: true,
RampTotal: len(resolved),
RampRunID: rampRunID,
DisplayName: taskName,
},
}
for _, t := range allTasks {
globalQueue.enqueue(t)
}
writeTaskRunResponse(w, allTasks)
globalQueue.enqueue(t)
writeTaskRunResponse(w, []*Task{t})
return
}
}
@@ -743,6 +737,9 @@ func (h *handler) handleAPISATAbort(w http.ResponseWriter, r *http.Request) {
if t.job != nil {
t.job.abort()
}
if taskMayLeaveOrphanWorkers(t.Target) {
platform.KillTestWorkers()
}
t.Status = TaskCancelled
now := time.Now()
t.DoneAt = &now

View File

@@ -72,6 +72,13 @@ tbody tr:hover td{background:rgba(0,0,0,.03)}
.badge-warn{background:var(--warn-bg);color:var(--warn-fg);border:1px solid #c9ba9b}
.badge-err{background:var(--crit-bg);color:var(--crit-fg);border:1px solid var(--crit-border)}
.badge-unknown{background:var(--surface-2);color:var(--muted);border:1px solid var(--border)}
/* Component chips — one small square per device */
.chips{display:inline-flex;flex-wrap:wrap;gap:3px;align-items:center;vertical-align:middle}
.chip{display:inline-flex;align-items:center;justify-content:center;width:20px;height:20px;border-radius:3px;font-size:10px;font-weight:800;cursor:default;font-family:monospace;letter-spacing:0;user-select:none}
.chip-ok{background:var(--ok-bg);color:var(--ok-fg);border:1px solid #a3c293}
.chip-warn{background:var(--warn-bg);color:var(--warn-fg);border:1px solid #c9ba9b}
.chip-fail{background:var(--crit-bg);color:var(--crit-fg);border:1px solid var(--crit-border)}
.chip-unknown{background:var(--surface-2);color:var(--muted);border:1px solid var(--border)}
/* Output terminal */
.terminal{background:#1b1c1d;border:1px solid rgba(0,0,0,.2);border-radius:4px;padding:14px;font-family:monospace;font-size:12px;color:#b5cea8;max-height:400px;overflow-y:auto;white-space:pre-wrap;word-break:break-all;user-select:text;-webkit-user-select:text}
.terminal-wrap{position:relative}.terminal-copy{position:absolute;top:6px;right:6px;background:#2d2f30;border:1px solid #444;color:#aaa;font-size:11px;padding:2px 8px;border-radius:3px;cursor:pointer;opacity:.7}.terminal-copy:hover{opacity:1}
@@ -363,23 +370,25 @@ func renderHardwareSummaryCard(opts HandlerOptions) string {
html.EscapeString(label), html.EscapeString(value), badgeHTML))
}
cpuRow := aggregateComponentStatus("CPU", records, []string{"cpu:all"}, nil)
writeRow("CPU", hwDescribeCPU(hw), runtimeStatusBadge(cpuRow.Status))
writeRow("CPU", hwDescribeCPU(hw),
renderComponentChips(matchedRecords(records, []string{"cpu:all"}, nil)))
memRow := aggregateComponentStatus("Memory", records, []string{"memory:all"}, []string{"memory:"})
writeRow("Memory", hwDescribeMemory(hw), runtimeStatusBadge(memRow.Status))
writeRow("Memory", hwDescribeMemory(hw),
renderComponentChips(matchedRecords(records, []string{"memory:all"}, []string{"memory:"})))
storageRow := aggregateComponentStatus("Storage", records, []string{"storage:all"}, []string{"storage:"})
writeRow("Storage", hwDescribeStorage(hw), runtimeStatusBadge(storageRow.Status))
writeRow("Storage", hwDescribeStorage(hw),
renderComponentChips(matchedRecords(records, []string{"storage:all"}, []string{"storage:"})))
gpuRow := aggregateComponentStatus("GPU", records, nil, []string{"pcie:gpu:"})
writeRow("GPU", hwDescribeGPU(hw), runtimeStatusBadge(gpuRow.Status))
writeRow("GPU", hwDescribeGPU(hw),
renderComponentChips(matchedRecords(records, nil, []string{"pcie:gpu:"})))
psuRow := aggregateComponentStatus("PSU", records, nil, []string{"psu:"})
if psuRow.Status == "UNKNOWN" && len(hw.PowerSupplies) > 0 {
psuRow.Status = hwPSUStatus(hw.PowerSupplies)
psuMatched := matchedRecords(records, nil, []string{"psu:"})
if len(psuMatched) == 0 && len(hw.PowerSupplies) > 0 {
// No PSU records yet — synthesise a single chip from IPMI status.
psuStatus := hwPSUStatus(hw.PowerSupplies)
psuMatched = []app.ComponentStatusRecord{{ComponentKey: "psu:ipmi", Status: psuStatus}}
}
writeRow("PSU", hwDescribePSU(hw), runtimeStatusBadge(psuRow.Status))
writeRow("PSU", hwDescribePSU(hw), renderComponentChips(psuMatched))
if nicDesc := hwDescribeNIC(hw); nicDesc != "" {
writeRow("Network", nicDesc, "")
@@ -892,6 +901,31 @@ func buildHardwareComponentRows(exportDir string) []runtimeHealthRow {
}
}
// matchedRecords returns all ComponentStatusRecord entries whose key matches
// any exact key or any of the given prefixes. Used for per-device chip rendering.
func firstNonEmpty(vals ...string) string {
for _, v := range vals {
if v != "" {
return v
}
}
return ""
}
func matchedRecords(records []app.ComponentStatusRecord, exact []string, prefixes []string) []app.ComponentStatusRecord {
var matched []app.ComponentStatusRecord
for _, rec := range records {
key := strings.TrimSpace(rec.ComponentKey)
if key == "" {
continue
}
if containsExactKey(key, exact) || hasAnyPrefix(key, prefixes) {
matched = append(matched, rec)
}
}
return matched
}
func aggregateComponentStatus(title string, records []app.ComponentStatusRecord, exact []string, prefixes []string) runtimeHealthRow {
matched := make([]app.ComponentStatusRecord, 0)
for _, rec := range records {
@@ -1034,6 +1068,52 @@ func runtimeIssueDescriptions(issues []schema.RuntimeIssue, codes ...string) str
return strings.Join(messages, "; ")
}
// chipLetterClass maps a component status to a single display letter and CSS class.
func chipLetterClass(status string) (letter, cls string) {
switch strings.ToUpper(strings.TrimSpace(status)) {
case "OK":
return "O", "chip-ok"
case "WARNING", "WARN", "PARTIAL":
return "W", "chip-warn"
case "CRITICAL", "FAIL", "FAILED", "ERROR":
return "F", "chip-fail"
default:
return "?", "chip-unknown"
}
}
// renderComponentChips renders one 20×20 chip per ComponentStatusRecord.
// Hover tooltip shows component key, status, error summary and last check time.
// Falls back to a single unknown chip when no records are available.
func renderComponentChips(matched []app.ComponentStatusRecord) string {
if len(matched) == 0 {
return `<span class="chips"><span class="chip chip-unknown" title="No data">?</span></span>`
}
sort.Slice(matched, func(i, j int) bool {
return matched[i].ComponentKey < matched[j].ComponentKey
})
var b strings.Builder
b.WriteString(`<span class="chips">`)
for _, rec := range matched {
letter, cls := chipLetterClass(rec.Status)
var tooltip strings.Builder
tooltip.WriteString(rec.ComponentKey)
tooltip.WriteString(": ")
tooltip.WriteString(firstNonEmpty(rec.Status, "UNKNOWN"))
if rec.ErrorSummary != "" {
tooltip.WriteString(" — ")
tooltip.WriteString(rec.ErrorSummary)
}
if !rec.LastCheckedAt.IsZero() {
fmt.Fprintf(&tooltip, " (checked %s)", rec.LastCheckedAt.Format("15:04:05"))
}
fmt.Fprintf(&b, `<span class="chip %s" title="%s">%s</span>`,
cls, html.EscapeString(tooltip.String()), letter)
}
b.WriteString(`</span>`)
return b.String()
}
func runtimeStatusBadge(status string) string {
status = strings.ToUpper(strings.TrimSpace(status))
badge := "badge-unknown"
@@ -1339,7 +1419,7 @@ func renderValidate(opts HandlerOptions) string {
inv.Memory,
`Runs a RAM validation pass and records memory state around the test.`,
`<code>free</code>, <code>memtester</code>`,
`256 MB / 1 pass in Validate, 1 GB / 3 passes in Stress.`,
`256 MB / 1 pass in Validate, 512 MB / 1 pass in Stress.`,
)) +
renderSATCard("storage", "Storage", "runSAT('storage')", "", renderValidateCardBody(
inv.Storage,
@@ -1401,7 +1481,7 @@ func renderValidate(opts HandlerOptions) string {
inv.NVIDIA,
`Verifies NVLink/NVSwitch fabric bandwidth using NCCL all_reduce_perf across all selected GPUs. Pass/fail based on achieved bandwidth vs. theoretical.`,
`<code>all_reduce_perf</code> (NCCL tests)`,
`Skipped in Validate mode. Runs in Stress mode only. Runs across all selected GPUs simultaneously (requires ≥2).<p id="sat-ni-mode-hint" style="color:var(--warn-fg);font-size:12px;margin:8px 0 0">Only runs in Stress mode. Switch mode above to enable in Run All.</p>`,
`Runs in Validate and Stress. Uses all selected GPUs simultaneously (requires ≥2) and is kept short so it fits the Validate flow.`,
)) +
`</div>` +
`<div id="sat-card-nvidia-bandwidth">` +
@@ -1409,7 +1489,7 @@ func renderValidate(opts HandlerOptions) string {
inv.NVIDIA,
`Validates GPU memory copy and peer-to-peer bandwidth paths using NVBandwidth.`,
`<code>nvbandwidth</code>`,
`Skipped in Validate mode. Runs in Stress mode only. Runs across all selected GPUs simultaneously.<p id="sat-nb-mode-hint" style="color:var(--warn-fg);font-size:12px;margin:8px 0 0">Only runs in Stress mode. Switch mode above to enable in Run All.</p>`,
`Runs in Validate and Stress across all selected GPUs simultaneously. Intended to stay short enough for Validate.`,
)) +
`</div>` +
`</div>
@@ -1447,8 +1527,6 @@ function satModeChanged() {
{card: 'sat-card-nvidia-targeted-stress', hint: 'sat-ts-mode-hint'},
{card: 'sat-card-nvidia-targeted-power', hint: 'sat-tp-mode-hint'},
{card: 'sat-card-nvidia-pulse', hint: 'sat-pt-mode-hint'},
{card: 'sat-card-nvidia-interconnect', hint: 'sat-ni-mode-hint'},
{card: 'sat-card-nvidia-bandwidth', hint: 'sat-nb-mode-hint'},
].forEach(function(item) {
const card = document.getElementById(item.card);
if (card) {
@@ -1696,7 +1774,7 @@ function runAllSAT() {
const cycles = 1;
const status = document.getElementById('sat-all-status');
status.textContent = 'Enqueuing...';
const stressOnlyTargets = ['nvidia-targeted-stress', 'nvidia-targeted-power', 'nvidia-pulse', 'nvidia-interconnect', 'nvidia-bandwidth'];
const stressOnlyTargets = ['nvidia-targeted-stress', 'nvidia-targeted-power', 'nvidia-pulse'];
const baseTargets = ['nvidia','nvidia-targeted-stress','nvidia-targeted-power','nvidia-pulse','nvidia-interconnect','nvidia-bandwidth','memory','storage','cpu'].concat(selectedAMDValidateTargets());
const activeTargets = baseTargets.filter(target => {
if (stressOnlyTargets.indexOf(target) >= 0 && !satStressMode()) return false;
@@ -1936,9 +2014,11 @@ func renderSATCard(id, label, runAction, headerActions, body string) string {
// ── Benchmark ─────────────────────────────────────────────────────────────────
type benchmarkHistoryRun struct {
generatedAt time.Time
displayTime string
gpuScores map[int]float64 // GPU index → composite score
generatedAt time.Time
displayTime string
gpuScores map[int]float64 // GPU index → composite score
gpuStatuses map[int]string // GPU index → status ("OK", "WARNING", "FAILED", …)
overallStatus string
}
func renderBenchmark(opts HandlerOptions) string {
@@ -2002,7 +2082,7 @@ func renderBenchmark(opts HandlerOptions) string {
</div>
</div>
`+`<div id="benchmark-results-section">`+renderBenchmarkResultsCard(opts.ExportDir)+`</div>`+`
` + `<div id="benchmark-results-section">` + renderBenchmarkResultsCard(opts.ExportDir) + `</div>` + `
<div id="benchmark-output" style="display:none;margin-top:16px" class="card">
<div class="card-head">Benchmark Output <span id="benchmark-title"></span></div>
@@ -2246,7 +2326,7 @@ 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>Run</th><th>Time</th>`)
b.WriteString(`<table><thead><tr><th>Run</th><th>Time</th><th>Status</th>`)
for i := 0; i <= maxGPUIndex; i++ {
b.WriteString(`<th>GPU ` + strconv.Itoa(i) + `</th>`)
}
@@ -2255,13 +2335,36 @@ func renderBenchmarkResultsCardFromRuns(title, description, emptyMessage string,
b.WriteString(`<tr>`)
b.WriteString(`<td>#` + strconv.Itoa(i+1) + `</td>`)
b.WriteString(`<td>` + html.EscapeString(run.displayTime) + `</td>`)
overallColor := "var(--ok)"
overallLabel := run.overallStatus
if overallLabel == "" {
overallLabel = "OK"
}
if overallLabel == "FAILED" {
overallColor = "var(--crit-fg,#9f3a38)"
} else if overallLabel != "OK" {
overallColor = "var(--warn)"
}
b.WriteString(`<td style="color:` + overallColor + `;font-weight:600">` + html.EscapeString(overallLabel) + `</td>`)
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", score) + `</td>`)
gpuStatus := run.gpuStatuses[idx]
scoreColor := ""
switch gpuStatus {
case "FAILED":
scoreColor = ` style="color:var(--crit-fg,#9f3a38);font-weight:600"`
case "WARNING", "PARTIAL":
scoreColor = ` style="color:var(--warn);font-weight:600"`
case "", "OK":
// no override
default:
scoreColor = ` style="color:var(--warn);font-weight:600"`
}
b.WriteString(`<td` + scoreColor + `>` + fmt.Sprintf("%.2f", score) + `</td>`)
}
b.WriteString(`</tr>`)
}
@@ -2295,12 +2398,15 @@ func loadBenchmarkHistoryFromPaths(paths []string) (int, []benchmarkHistoryRun)
continue
}
run := benchmarkHistoryRun{
generatedAt: result.GeneratedAt,
displayTime: result.GeneratedAt.Local().Format("2006-01-02 15:04:05"),
gpuScores: make(map[int]float64),
generatedAt: result.GeneratedAt,
displayTime: result.GeneratedAt.Local().Format("2006-01-02 15:04:05"),
gpuScores: make(map[int]float64),
gpuStatuses: make(map[int]string),
overallStatus: result.OverallStatus,
}
for _, gpu := range result.GPUs {
run.gpuScores[gpu.Index] = gpu.Scores.CompositeScore
run.gpuStatuses[gpu.Index] = gpu.Status
if gpu.Index > maxGPUIndex {
maxGPUIndex = gpu.Index
}
@@ -2369,31 +2475,45 @@ func renderPowerBenchmarkResultsCard(exportDir string) string {
if len(latest.GPUs) > 0 {
b.WriteString(`<div style="overflow-x:auto"><table><thead><tr>`)
b.WriteString(`<th>GPU</th><th>Model</th><th>Nominal W</th><th>Achieved W</th><th>P95 Observed W</th><th>Status</th>`)
b.WriteString(`<th>GPU</th><th>Model</th><th>Nominal W</th><th>Single-card W</th><th>Multi-GPU W</th><th>P95 Observed W</th><th>Status</th>`)
b.WriteString(`</tr></thead><tbody>`)
for _, gpu := range latest.GPUs {
derated := gpu.Derated || (gpu.DefaultPowerLimitW > 0 && gpu.AppliedPowerLimitW < gpu.DefaultPowerLimitW-1)
// finalLimitW is the definitive TDP: multi-GPU stable limit from the ramp,
// falling back to single-card applied limit if the ramp hasn't run.
finalLimitW := gpu.StablePowerLimitW
if finalLimitW <= 0 {
finalLimitW = gpu.AppliedPowerLimitW
}
// Derate is relative to nominal (DefaultPowerLimitW), using the final limit.
derated := gpu.Derated ||
(gpu.DefaultPowerLimitW > 0 && finalLimitW > 0 && finalLimitW < gpu.DefaultPowerLimitW-1)
rowStyle := ""
achievedStyle := ""
finalStyle := ""
if derated {
rowStyle = ` style="background:rgba(255,180,0,0.08)"`
achievedStyle = ` style="color:#e6a000;font-weight:600"`
finalStyle = ` style="color:#e6a000;font-weight:600"`
}
statusLabel := gpu.Status
if statusLabel == "" {
statusLabel = "OK"
}
statusColor := "var(--ok)"
if statusLabel != "OK" {
if statusLabel == "FAILED" {
statusColor = "var(--crit-fg,#9f3a38)"
} else if statusLabel != "OK" {
statusColor = "var(--warn)"
}
nominalStr := "-"
if gpu.DefaultPowerLimitW > 0 {
nominalStr = fmt.Sprintf("%.0f", gpu.DefaultPowerLimitW)
}
achievedStr := "-"
singleStr := "-"
if gpu.AppliedPowerLimitW > 0 {
achievedStr = fmt.Sprintf("%.0f", gpu.AppliedPowerLimitW)
singleStr = fmt.Sprintf("%.0f", gpu.AppliedPowerLimitW)
}
multiStr := "-"
if gpu.StablePowerLimitW > 0 {
multiStr = fmt.Sprintf("%.0f", gpu.StablePowerLimitW)
}
p95Str := "-"
if gpu.MaxObservedPowerW > 0 {
@@ -2403,7 +2523,8 @@ func renderPowerBenchmarkResultsCard(exportDir string) string {
b.WriteString(`<td>` + strconv.Itoa(gpu.Index) + `</td>`)
b.WriteString(`<td>` + html.EscapeString(gpu.Name) + `</td>`)
b.WriteString(`<td>` + nominalStr + `</td>`)
b.WriteString(`<td` + achievedStyle + `>` + achievedStr + `</td>`)
b.WriteString(`<td>` + singleStr + `</td>`)
b.WriteString(`<td` + finalStyle + `>` + multiStr + `</td>`)
b.WriteString(`<td>` + p95Str + `</td>`)
b.WriteString(`<td style="color:` + statusColor + `;font-weight:600">` + html.EscapeString(statusLabel) + `</td>`)
b.WriteString(`</tr>`)
@@ -2437,7 +2558,7 @@ func renderPowerBenchmarkResultsCard(exportDir string) string {
func renderBurn() string {
return `<div class="alert alert-warn" style="margin-bottom:16px"><strong>&#9888; Warning:</strong> Stress tests on this page run hardware at high load. Repeated or prolonged use may reduce hardware lifespan. Use only when necessary.</div>
<div class="alert alert-info" style="margin-bottom:16px"><strong>Scope:</strong> DCGM diagnostics (` + "targeted_stress, targeted_power, pulse_test" + `), NCCL, NVBandwidth, and LINPACK remain in <a href="/validate">Validate → Stress mode</a>. Burn exposes sustained GPU compute load recipes.</div>
<div class="alert alert-info" style="margin-bottom:16px"><strong>Scope:</strong> Burn exposes sustained GPU compute load recipes. DCGM diagnostics (` + "targeted_stress, targeted_power, pulse_test" + `) and LINPACK remain in <a href="/validate">Validate → Stress mode</a>; NCCL and NVBandwidth are available directly from <a href="/validate">Validate</a>.</div>
<p style="color:var(--muted);font-size:13px;margin-bottom:16px">Tasks continue in the background — view progress in <a href="/tasks">Tasks</a>.</p>
<div class="card" style="margin-bottom:16px">

View File

@@ -744,6 +744,26 @@ func TestValidatePageRendersNvidiaTargetedStressCard(t *testing.T) {
}
}
func TestValidatePageRendersNvidiaFabricCardsInValidateMode(t *testing.T) {
handler := NewHandler(HandlerOptions{})
rec := httptest.NewRecorder()
handler.ServeHTTP(rec, httptest.NewRequest(http.MethodGet, "/validate", nil))
if rec.Code != http.StatusOK {
t.Fatalf("status=%d", rec.Code)
}
body := rec.Body.String()
for _, needle := range []string{
`NVIDIA Interconnect (NCCL)`,
`Runs in Validate and Stress.`,
`NVIDIA Bandwidth (NVBandwidth)`,
`Intended to stay short enough for Validate.`,
} {
if !strings.Contains(body, needle) {
t.Fatalf("validate page missing %q: %s", needle, body)
}
}
}
func TestBurnPageRendersGoalBasedNVIDIACards(t *testing.T) {
handler := NewHandler(HandlerOptions{})
rec := httptest.NewRecorder()

View File

@@ -162,6 +162,32 @@ type nvidiaRampSpec struct {
TotalDurationSec int
}
func resolveMemoryValidatePreset(profile string, stress bool) (sizeMB, passes int) {
switch strings.TrimSpace(strings.ToLower(profile)) {
case "overnight":
return 1024, 2
case "acceptance":
return 1024, 1
case "smoke":
return 256, 1
}
if stress {
return 512, 1
}
return 256, 1
}
func taskMayLeaveOrphanWorkers(target string) bool {
switch strings.TrimSpace(strings.ToLower(target)) {
case "nvidia", "nvidia-targeted-stress", "nvidia-targeted-power", "nvidia-pulse",
"nvidia-bandwidth", "nvidia-stress", "nvidia-compute", "nvidia-bench-perf",
"memory", "memory-stress", "cpu", "sat-stress", "platform-stress":
return true
default:
return false
}
}
func resolveBurnPreset(profile string) burnPreset {
switch profile {
case "overnight":
@@ -710,15 +736,7 @@ func (q *taskQueue) runTask(t *Task, j *jobState, ctx context.Context) {
err = fmt.Errorf("app not configured")
break
}
dur := t.params.Duration
if t.params.BurnProfile != "" && dur <= 0 {
dur = resolveBurnPreset(t.params.BurnProfile).DurationSec
}
archive, err = runNvidiaStressPackCtx(a, ctx, "", platform.NvidiaStressOptions{
DurationSec: dur,
Loader: platform.NvidiaStressLoaderNCCL,
GPUIndices: t.params.GPUIndices,
}, j.append)
archive, err = a.RunNCCLTests(ctx, "", t.params.GPUIndices, j.append)
case "nvidia-stress":
if a == nil {
err = fmt.Errorf("app not configured")
@@ -751,10 +769,8 @@ func (q *taskQueue) runTask(t *Task, j *jobState, ctx context.Context) {
err = fmt.Errorf("app not configured")
break
}
sizeMB, passes := 256, 1
if t.params.StressMode {
sizeMB, passes = 1024, 3
}
sizeMB, passes := resolveMemoryValidatePreset(t.params.BurnProfile, t.params.StressMode)
j.append(fmt.Sprintf("Memory validate preset: %d MB x %d pass(es)", sizeMB, passes))
archive, err = runMemoryAcceptancePackCtx(a, ctx, "", sizeMB, passes, j.append)
case "storage":
if a == nil {
@@ -1010,6 +1026,9 @@ func (h *handler) handleAPITasksCancelAll(w http.ResponseWriter, _ *http.Request
if t.job != nil {
t.job.abort()
}
if taskMayLeaveOrphanWorkers(t.Target) {
platform.KillTestWorkers()
}
t.Status = TaskCancelled
t.DoneAt = &now
taskSerialEvent(t, "finished with status="+t.Status)
@@ -1037,6 +1056,9 @@ func (h *handler) handleAPITasksKillWorkers(w http.ResponseWriter, _ *http.Reque
if t.job != nil {
t.job.abort()
}
if taskMayLeaveOrphanWorkers(t.Target) {
platform.KillTestWorkers()
}
t.Status = TaskCancelled
t.DoneAt = &now
taskSerialEvent(t, "finished with status="+t.Status)
@@ -1141,10 +1163,13 @@ func (q *taskQueue) loadLocked() {
q.assignTaskLogPathLocked(t)
if t.Status == TaskRunning {
// The task was interrupted by a bee-web restart. Child processes
// (e.g. bee-gpu-burn-worker) survive the restart in their own
// process groups and cannot be cancelled retroactively. Mark the
// task as failed so the user can decide whether to re-run it
// rather than blindly re-launching duplicate workers.
// (e.g. bee-gpu-burn-worker, dcgmi/nvvs) survive the restart in
// their own process groups. Kill any matching stale workers before
// marking the task failed so the next GPU test does not inherit a
// busy DCGM slot or duplicate workers.
if taskMayLeaveOrphanWorkers(t.Target) {
_ = platform.KillTestWorkers()
}
now := time.Now()
t.Status = TaskFailed
t.DoneAt = &now

View File

@@ -672,6 +672,36 @@ func TestRunTaskUsesBurnProfileDurationForCPU(t *testing.T) {
}
}
func TestRunTaskUsesQuickPresetForMemoryValidate(t *testing.T) {
var gotSizeMB, gotPasses int
q := &taskQueue{
opts: &HandlerOptions{App: &app.App{}},
}
tk := &Task{
ID: "mem-validate-1",
Name: "Memory SAT",
Target: "memory",
Status: TaskRunning,
CreatedAt: time.Now(),
params: taskParams{StressMode: true},
}
j := &jobState{}
orig := runMemoryAcceptancePackCtx
runMemoryAcceptancePackCtx = func(_ *app.App, _ context.Context, _ string, sizeMB, passes int, _ func(string)) (string, error) {
gotSizeMB = sizeMB
gotPasses = passes
return "/tmp/memory-validate.tar.gz", nil
}
defer func() { runMemoryAcceptancePackCtx = orig }()
q.runTask(tk, j, context.Background())
if gotSizeMB != 512 || gotPasses != 1 {
t.Fatalf("memory validate preset=%dMB x%d want 512MB x1", gotSizeMB, gotPasses)
}
}
func TestRunTaskBuildsSupportBundleWithoutApp(t *testing.T) {
dir := t.TempDir()
q := &taskQueue{

View File

@@ -1,6 +1,7 @@
DEBIAN_VERSION=12
DEBIAN_KERNEL_ABI=auto
NVIDIA_DRIVER_VERSION=590.48.01
NVIDIA_FABRICMANAGER_VERSION=590.48.01-1
NCCL_VERSION=2.28.9-1
NCCL_CUDA_VERSION=13.0
NCCL_SHA256=2e6faafd2c19cffc7738d9283976a3200ea9db9895907f337f0c7e5a25563186

View File

@@ -33,6 +33,7 @@ lb config noauto \
--iso-volume "EASY_BEE_${BEE_GPU_VENDOR_UPPER:-NVIDIA}" \
--iso-application "EASY-BEE-${BEE_GPU_VENDOR_UPPER:-NVIDIA}" \
--bootappend-live "boot=live components video=1920x1080 console=tty0 console=ttyS0,115200n8 loglevel=3 systemd.show_status=1 username=bee user-fullname=Bee modprobe.blacklist=nouveau,snd_hda_intel,snd_hda_codec_realtek,snd_hda_codec_generic,soundcore" \
--debootstrap-options "--include=ca-certificates" \
--apt-recommends false \
--chroot-squashfs-compression-type zstd \
"${@}"

View File

@@ -35,6 +35,8 @@ typedef void *CUstream;
#define MAX_STRESS_STREAMS 16
#define MIN_PROFILE_BUDGET_BYTES ((size_t)4u * 1024u * 1024u)
#define MIN_STREAM_BUDGET_BYTES ((size_t)64u * 1024u * 1024u)
#define MAX_SINGLE_PRECISION_STREAMS 4
#define MAX_SINGLE_PRECISION_PROFILE_BUDGET_BYTES ((size_t)2u * 1024u * 1024u * 1024u)
static const char *ptx_source =
".version 6.0\n"
@@ -296,6 +298,13 @@ static int choose_stream_count(int mp_count, int planned_profiles, size_t total_
return stream_count;
}
static size_t clamp_single_precision_profile_budget(size_t profile_budget_bytes) {
if (profile_budget_bytes > MAX_SINGLE_PRECISION_PROFILE_BUDGET_BYTES) {
return MAX_SINGLE_PRECISION_PROFILE_BUDGET_BYTES;
}
return profile_budget_bytes;
}
static void destroy_streams(struct cuda_api *api, CUstream *streams, int count) {
if (!api->cuStreamDestroy) {
return;
@@ -704,6 +713,19 @@ static const struct profile_desc k_profiles[] = {
#define PROFILE_COUNT ((int)(sizeof(k_profiles) / sizeof(k_profiles[0])))
static int profile_allowed_for_run(const struct profile_desc *desc, int cc, const char *precision_filter) {
if (!(desc->enabled && cc >= desc->min_cc)) {
return 0;
}
if (precision_filter != NULL) {
return strcmp(desc->block_label, precision_filter) == 0;
}
/* Mixed/all phases intentionally exclude fp64/fp4 for now: both paths are
* unstable on the current benchmark fleet and can abort the whole mixed
* pass after earlier phases already collected useful telemetry. */
return strcmp(desc->block_label, "fp64") != 0 && strcmp(desc->block_label, "fp4") != 0;
}
static int load_cublaslt(struct cublaslt_api *api) {
memset(api, 0, sizeof(*api));
api->lib = dlopen("libcublasLt.so.13", RTLD_NOW | RTLD_LOCAL);
@@ -908,11 +930,9 @@ static int prepare_profile(struct cublaslt_api *cublas,
CUstream stream,
size_t profile_budget_bytes,
struct prepared_profile *out) {
memset(out, 0, sizeof(*out));
out->desc = *desc;
out->stream = stream;
size_t bytes_per_cell = 0;
size_t attempt_budget = profile_budget_bytes;
bytes_per_cell += bytes_for_elements(desc->a_type, 1);
bytes_per_cell += bytes_for_elements(desc->b_type, 1);
bytes_per_cell += bytes_for_elements(desc->c_type, 1);
@@ -921,106 +941,115 @@ static int prepare_profile(struct cublaslt_api *cublas,
return 0;
}
uint64_t dim = choose_square_dim(profile_budget_bytes, bytes_per_cell, desc->min_multiple);
out->m = dim;
out->n = dim;
out->k = dim;
while (attempt_budget >= MIN_PROFILE_BUDGET_BYTES) {
memset(out, 0, sizeof(*out));
out->desc = *desc;
out->stream = stream;
size_t desired_workspace = profile_budget_bytes / 8u;
if (desired_workspace > 32u * 1024u * 1024u) {
desired_workspace = 32u * 1024u * 1024u;
}
desired_workspace = round_down_size(desired_workspace, 256u);
uint64_t dim = choose_square_dim(attempt_budget, bytes_per_cell, desc->min_multiple);
out->m = dim;
out->n = dim;
out->k = dim;
size_t a_bytes = 0;
size_t b_bytes = 0;
size_t c_bytes = 0;
size_t d_bytes = 0;
size_t scale_bytes = 0;
while (1) {
a_bytes = bytes_for_elements(desc->a_type, out->k * out->m);
b_bytes = bytes_for_elements(desc->b_type, out->k * out->n);
c_bytes = bytes_for_elements(desc->c_type, out->m * out->n);
d_bytes = bytes_for_elements(desc->d_type, out->m * out->n);
scale_bytes = profile_scale_bytes(desc, out->m, out->n, out->k);
size_t desired_workspace = attempt_budget / 8u;
if (desired_workspace > 32u * 1024u * 1024u) {
desired_workspace = 32u * 1024u * 1024u;
}
desired_workspace = round_down_size(desired_workspace, 256u);
size_t matrix_bytes = a_bytes + b_bytes + c_bytes + d_bytes + scale_bytes;
if (matrix_bytes <= profile_budget_bytes) {
size_t remaining = profile_budget_bytes - matrix_bytes;
out->workspace_size = desired_workspace;
if (out->workspace_size > remaining) {
out->workspace_size = round_down_size(remaining, 256u);
size_t a_bytes = 0;
size_t b_bytes = 0;
size_t c_bytes = 0;
size_t d_bytes = 0;
size_t scale_bytes = 0;
while (1) {
a_bytes = bytes_for_elements(desc->a_type, out->k * out->m);
b_bytes = bytes_for_elements(desc->b_type, out->k * out->n);
c_bytes = bytes_for_elements(desc->c_type, out->m * out->n);
d_bytes = bytes_for_elements(desc->d_type, out->m * out->n);
scale_bytes = profile_scale_bytes(desc, out->m, out->n, out->k);
size_t matrix_bytes = a_bytes + b_bytes + c_bytes + d_bytes + scale_bytes;
if (matrix_bytes <= attempt_budget) {
size_t remaining = attempt_budget - matrix_bytes;
out->workspace_size = desired_workspace;
if (out->workspace_size > remaining) {
out->workspace_size = round_down_size(remaining, 256u);
}
break;
}
break;
if (out->m <= (uint64_t)desc->min_multiple) {
break;
}
out->m -= (uint64_t)desc->min_multiple;
out->n = out->m;
out->k = out->m;
}
if (out->m < (uint64_t)desc->min_multiple) {
attempt_budget /= 2u;
continue;
}
if (out->m <= (uint64_t)desc->min_multiple) {
return 0;
}
out->m -= (uint64_t)desc->min_multiple;
out->n = out->m;
out->k = out->m;
}
if (!alloc_filled(cuda, &out->a_dev, a_bytes, 0x11) ||
!alloc_filled(cuda, &out->b_dev, b_bytes, 0x11) ||
!alloc_filled(cuda, &out->c_dev, c_bytes, 0x00) ||
!alloc_filled(cuda, &out->d_dev, d_bytes, 0x00)) {
destroy_profile(cublas, cuda, out);
return 0;
}
cudaDataType_t scale_type = matmul_scale_type(desc);
if (!check_cublas("cublasLtMatmulDescCreate",
cublas->cublasLtMatmulDescCreate(&out->op_desc, desc->compute_type, scale_type))) {
destroy_profile(cublas, cuda, out);
return 0;
}
cublasOperation_t transa = CUBLAS_OP_T;
cublasOperation_t transb = CUBLAS_OP_N;
if (!check_cublas("set TRANSA",
cublas->cublasLtMatmulDescSetAttribute(out->op_desc,
CUBLASLT_MATMUL_DESC_TRANSA,
&transa,
sizeof(transa))) ||
!check_cublas("set TRANSB",
cublas->cublasLtMatmulDescSetAttribute(out->op_desc,
CUBLASLT_MATMUL_DESC_TRANSB,
&transb,
sizeof(transb)))) {
destroy_profile(cublas, cuda, out);
return 0;
}
if (desc->needs_scalar_scale) {
float one = 1.0f;
if (!alloc_filled(cuda, &out->a_scale_dev, sizeof(one), 0x00) ||
!alloc_filled(cuda, &out->b_scale_dev, sizeof(one), 0x00)) {
if (!alloc_filled(cuda, &out->a_dev, a_bytes, 0x11) ||
!alloc_filled(cuda, &out->b_dev, b_bytes, 0x11) ||
!alloc_filled(cuda, &out->c_dev, c_bytes, 0x00) ||
!alloc_filled(cuda, &out->d_dev, d_bytes, 0x00)) {
destroy_profile(cublas, cuda, out);
return 0;
}
if (!device_upload(cuda, out->a_scale_dev, &one, sizeof(one)) ||
!device_upload(cuda, out->b_scale_dev, &one, sizeof(one))) {
cudaDataType_t scale_type = matmul_scale_type(desc);
if (!check_cublas("cublasLtMatmulDescCreate",
cublas->cublasLtMatmulDescCreate(&out->op_desc, desc->compute_type, scale_type))) {
destroy_profile(cublas, cuda, out);
return 0;
}
void *a_scale_ptr = (void *)(uintptr_t)out->a_scale_dev;
void *b_scale_ptr = (void *)(uintptr_t)out->b_scale_dev;
if (!check_cublas("set A scale ptr",
cublasOperation_t transa = CUBLAS_OP_T;
cublasOperation_t transb = CUBLAS_OP_N;
if (!check_cublas("set TRANSA",
cublas->cublasLtMatmulDescSetAttribute(out->op_desc,
CUBLASLT_MATMUL_DESC_A_SCALE_POINTER,
&a_scale_ptr,
sizeof(a_scale_ptr))) ||
!check_cublas("set B scale ptr",
CUBLASLT_MATMUL_DESC_TRANSA,
&transa,
sizeof(transa))) ||
!check_cublas("set TRANSB",
cublas->cublasLtMatmulDescSetAttribute(out->op_desc,
CUBLASLT_MATMUL_DESC_B_SCALE_POINTER,
&b_scale_ptr,
sizeof(b_scale_ptr)))) {
CUBLASLT_MATMUL_DESC_TRANSB,
&transb,
sizeof(transb)))) {
destroy_profile(cublas, cuda, out);
return 0;
}
}
if (desc->needs_scalar_scale) {
float one = 1.0f;
if (!alloc_filled(cuda, &out->a_scale_dev, sizeof(one), 0x00) ||
!alloc_filled(cuda, &out->b_scale_dev, sizeof(one), 0x00)) {
destroy_profile(cublas, cuda, out);
return 0;
}
if (!device_upload(cuda, out->a_scale_dev, &one, sizeof(one)) ||
!device_upload(cuda, out->b_scale_dev, &one, sizeof(one))) {
destroy_profile(cublas, cuda, out);
return 0;
}
void *a_scale_ptr = (void *)(uintptr_t)out->a_scale_dev;
void *b_scale_ptr = (void *)(uintptr_t)out->b_scale_dev;
if (!check_cublas("set A scale ptr",
cublas->cublasLtMatmulDescSetAttribute(out->op_desc,
CUBLASLT_MATMUL_DESC_A_SCALE_POINTER,
&a_scale_ptr,
sizeof(a_scale_ptr))) ||
!check_cublas("set B scale ptr",
cublas->cublasLtMatmulDescSetAttribute(out->op_desc,
CUBLASLT_MATMUL_DESC_B_SCALE_POINTER,
&b_scale_ptr,
sizeof(b_scale_ptr)))) {
destroy_profile(cublas, cuda, out);
return 0;
}
}
#if defined(CUBLASLT_MATMUL_MATRIX_SCALE_VEC16_UE4M3)
if (desc->needs_block_scale) {
@@ -1060,62 +1089,65 @@ static int prepare_profile(struct cublaslt_api *cublas,
}
#endif
if (!check_cublas("create A layout",
cublas->cublasLtMatrixLayoutCreate(&out->a_layout, desc->a_type, out->k, out->m, out->k)) ||
!check_cublas("create B layout",
cublas->cublasLtMatrixLayoutCreate(&out->b_layout, desc->b_type, out->k, out->n, out->k)) ||
!check_cublas("create C layout",
cublas->cublasLtMatrixLayoutCreate(&out->c_layout, desc->c_type, out->m, out->n, out->m)) ||
!check_cublas("create D layout",
cublas->cublasLtMatrixLayoutCreate(&out->d_layout, desc->d_type, out->m, out->n, out->m))) {
destroy_profile(cublas, cuda, out);
return 0;
}
if (!check_cublas("create preference", cublas->cublasLtMatmulPreferenceCreate(&out->preference))) {
destroy_profile(cublas, cuda, out);
return 0;
}
if (out->workspace_size > 0) {
if (!alloc_filled(cuda, &out->workspace_dev, out->workspace_size, 0x00)) {
if (!check_cublas("create A layout",
cublas->cublasLtMatrixLayoutCreate(&out->a_layout, desc->a_type, out->k, out->m, out->k)) ||
!check_cublas("create B layout",
cublas->cublasLtMatrixLayoutCreate(&out->b_layout, desc->b_type, out->k, out->n, out->k)) ||
!check_cublas("create C layout",
cublas->cublasLtMatrixLayoutCreate(&out->c_layout, desc->c_type, out->m, out->n, out->m)) ||
!check_cublas("create D layout",
cublas->cublasLtMatrixLayoutCreate(&out->d_layout, desc->d_type, out->m, out->n, out->m))) {
destroy_profile(cublas, cuda, out);
return 0;
}
if (!check_cublas("create preference", cublas->cublasLtMatmulPreferenceCreate(&out->preference))) {
destroy_profile(cublas, cuda, out);
return 0;
}
if (out->workspace_size > 0) {
if (!alloc_filled(cuda, &out->workspace_dev, out->workspace_size, 0x00)) {
destroy_profile(cublas, cuda, out);
return 0;
}
}
if (!check_cublas("set workspace",
cublas->cublasLtMatmulPreferenceSetAttribute(
out->preference,
CUBLASLT_MATMUL_PREF_MAX_WORKSPACE_BYTES,
&out->workspace_size,
sizeof(out->workspace_size)))) {
destroy_profile(cublas, cuda, out);
return 0;
}
int found = 0;
if (check_cublas("heuristic",
cublas->cublasLtMatmulAlgoGetHeuristic(handle,
out->op_desc,
out->a_layout,
out->b_layout,
out->c_layout,
out->d_layout,
out->preference,
1,
&out->heuristic,
&found)) &&
found > 0) {
out->ready = 1;
return 1;
}
destroy_profile(cublas, cuda, out);
attempt_budget = round_down_size(attempt_budget * 3u / 4u, 256u);
if (attempt_budget < MIN_PROFILE_BUDGET_BYTES) {
break;
}
}
if (!check_cublas("set workspace",
cublas->cublasLtMatmulPreferenceSetAttribute(
out->preference,
CUBLASLT_MATMUL_PREF_MAX_WORKSPACE_BYTES,
&out->workspace_size,
sizeof(out->workspace_size)))) {
destroy_profile(cublas, cuda, out);
return 0;
}
int found = 0;
if (!check_cublas("heuristic",
cublas->cublasLtMatmulAlgoGetHeuristic(handle,
out->op_desc,
out->a_layout,
out->b_layout,
out->c_layout,
out->d_layout,
out->preference,
1,
&out->heuristic,
&found))) {
destroy_profile(cublas, cuda, out);
return 0;
}
if (found <= 0) {
destroy_profile(cublas, cuda, out);
return 0;
}
out->ready = 1;
return 1;
return 0;
}
static int run_cublas_profile(cublasLtHandle_t handle,
@@ -1180,6 +1212,7 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
size_t requested_budget = 0;
size_t total_budget = 0;
size_t per_profile_budget = 0;
int budget_profiles = 0;
memset(report, 0, sizeof(*report));
snprintf(report->backend, sizeof(report->backend), "cublasLt");
@@ -1202,8 +1235,7 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
/* 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 &&
(precision_filter == NULL || strcmp(k_profiles[i].block_label, precision_filter) == 0)) {
if (profile_allowed_for_run(&k_profiles[i], cc, precision_filter)) {
planned++;
}
}
@@ -1215,30 +1247,41 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
}
/* 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. */
* Mixed phases still divide budget across the full precision set, while
* single-precision benchmark phases dedicate budget only to active
* profiles matching precision_filter. */
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) {
if (profile_allowed_for_run(&k_profiles[i], cc, precision_filter)) {
planned_total++;
}
}
if (planned_total < planned) {
planned_total = planned;
}
budget_profiles = planned_total;
if (precision_filter != NULL) {
budget_profiles = planned;
}
if (budget_profiles <= 0) {
budget_profiles = planned_total;
}
requested_budget = (size_t)size_mb * 1024u * 1024u;
if (requested_budget < (size_t)planned_total * MIN_PROFILE_BUDGET_BYTES) {
requested_budget = (size_t)planned_total * MIN_PROFILE_BUDGET_BYTES;
if (requested_budget < (size_t)budget_profiles * MIN_PROFILE_BUDGET_BYTES) {
requested_budget = (size_t)budget_profiles * MIN_PROFILE_BUDGET_BYTES;
}
total_budget = clamp_budget_to_free_memory(cuda, requested_budget);
if (total_budget < (size_t)planned_total * MIN_PROFILE_BUDGET_BYTES) {
total_budget = (size_t)planned_total * MIN_PROFILE_BUDGET_BYTES;
if (total_budget < (size_t)budget_profiles * MIN_PROFILE_BUDGET_BYTES) {
total_budget = (size_t)budget_profiles * 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, total_budget, 1);
stream_count = choose_stream_count(mp_count, budget_profiles, total_budget, 1);
}
if (precision_filter != NULL && stream_count > MAX_SINGLE_PRECISION_STREAMS) {
stream_count = MAX_SINGLE_PRECISION_STREAMS;
}
if (stream_count > 1) {
int created = 0;
@@ -1251,18 +1294,22 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
}
}
report->stream_count = stream_count;
per_profile_budget = total_budget / ((size_t)planned_total * (size_t)stream_count);
per_profile_budget = total_budget / ((size_t)budget_profiles * (size_t)stream_count);
if (per_profile_budget < MIN_PROFILE_BUDGET_BYTES) {
per_profile_budget = MIN_PROFILE_BUDGET_BYTES;
}
if (precision_filter != NULL) {
per_profile_budget = clamp_single_precision_profile_budget(per_profile_budget);
}
report->buffer_mb = (int)(total_budget / (1024u * 1024u));
append_detail(report->details,
sizeof(report->details),
"requested_mb=%d actual_mb=%d streams=%d mp_count=%d per_worker_mb=%zu\n",
"requested_mb=%d actual_mb=%d streams=%d mp_count=%d budget_profiles=%d per_worker_mb=%zu\n",
size_mb,
report->buffer_mb,
report->stream_count,
mp_count,
budget_profiles,
per_profile_budget / (1024u * 1024u));
for (int i = 0; i < profile_count; i++) {
@@ -1275,10 +1322,10 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
desc->min_cc);
continue;
}
if (precision_filter != NULL && strcmp(desc->block_label, precision_filter) != 0) {
if (!profile_allowed_for_run(desc, cc, precision_filter)) {
append_detail(report->details,
sizeof(report->details),
"%s=SKIPPED precision_filter\n",
"%s=SKIPPED benchmark_disabled\n",
desc->name);
continue;
}

View File

@@ -1262,6 +1262,7 @@ fi
# --- substitute version placeholders in package list and archive ---
if [ "$BEE_GPU_VENDOR" = "nvidia" ]; then
sed -i \
-e "s/%%NVIDIA_FABRICMANAGER_VERSION%%/${NVIDIA_FABRICMANAGER_VERSION}/g" \
-e "s/%%DCGM_VERSION%%/${DCGM_VERSION}/g" \
"${BUILD_WORK_DIR}/config/package-lists/bee-gpu.list.chroot"
elif [ "$BEE_GPU_VENDOR" = "amd" ]; then
@@ -1304,7 +1305,7 @@ BEE_GPU_VENDOR_UPPER="$(echo "${BUILD_VARIANT}" | tr 'a-z-' 'A-Z_')"
export BEE_GPU_VENDOR_UPPER
cd "${LB_DIR}"
run_step_sh "live-build clean" "80-lb-clean" "lb clean 2>&1 | tail -3"
run_step_sh "live-build clean" "80-lb-clean" "lb clean --all 2>&1 | tail -3"
run_step_sh "live-build config" "81-lb-config" "lb config 2>&1 | tail -5"
dump_memtest_debug "pre-build" "${LB_DIR}"
run_step_sh "live-build build" "90-lb-build" "lb build 2>&1"

View File

@@ -43,6 +43,7 @@ systemctl enable bee-journal-mirror@ttyS1.service 2>/dev/null || true
# Enable GPU-vendor specific services
if [ "$GPU_VENDOR" = "nvidia" ]; then
systemctl enable nvidia-dcgm.service 2>/dev/null || true
systemctl enable nvidia-fabricmanager.service 2>/dev/null || true
systemctl enable bee-nvidia.service
elif [ "$GPU_VENDOR" = "amd" ]; then
# ROCm symlinks (packages install to /opt/rocm-*/bin/)

View File

@@ -1,117 +0,0 @@
#!/bin/sh
# 9001-wallpaper.hook.chroot — generate /usr/share/bee/wallpaper.png inside chroot
set -e
echo "=== generating bee wallpaper ==="
mkdir -p /usr/share/bee
python3 - <<'PYEOF'
from PIL import Image, ImageDraw, ImageFont, ImageFilter
import os
W, H = 1920, 1080
ASCII_ART = [
" ███████╗ █████╗ ███████╗██╗ ██╗ ██████╗ ███████╗███████╗",
" ██╔════╝██╔══██╗██╔════╝╚██╗ ██╔╝ ██╔══██╗██╔════╝██╔════╝",
" █████╗ ███████║███████╗ ╚████╔╝ █████╗██████╔╝█████╗ █████╗",
" ██╔══╝ ██╔══██║╚════██║ ╚██╔╝ ╚════╝██╔══██╗██╔══╝ ██╔══╝",
" ███████╗██║ ██║███████║ ██║ ██████╔╝███████╗███████╗",
" ╚══════╝╚═╝ ╚═╝╚══════╝ ╚═╝ ╚═════╝ ╚══════╝╚══════╝",
]
SUBTITLE = " Hardware Audit LiveCD"
FG = (0xF6, 0xD0, 0x47)
FG_DIM = (0xD4, 0xA9, 0x1C)
SHADOW = (0x5E, 0x47, 0x05)
SUB = (0x96, 0x7A, 0x17)
BG = (0x05, 0x05, 0x05)
MONO_FONT_CANDIDATES = [
'/usr/share/fonts/truetype/dejavu/DejaVuSansMono-Bold.ttf',
'/usr/share/fonts/truetype/liberation2/LiberationMono-Bold.ttf',
'/usr/share/fonts/truetype/liberation/LiberationMono-Bold.ttf',
'/usr/share/fonts/truetype/freefont/FreeMonoBold.ttf',
]
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',
]
def load_font(candidates, size):
for path in candidates:
if os.path.exists(path):
return ImageFont.truetype(path, size)
return ImageFont.load_default()
def mono_metrics(font):
probe = Image.new('L', (W, H), 0)
draw = ImageDraw.Draw(probe)
char_w = int(round(draw.textlength("M", font=font)))
bb = draw.textbbox((0, 0), "Mg", font=font)
char_h = bb[3] - bb[1]
return char_w, char_h
def render_ascii_mask(font, lines, char_w, char_h, line_gap):
width = max(len(line) for line in lines) * char_w
height = len(lines) * char_h + line_gap * (len(lines) - 1)
mask = Image.new('L', (width, height), 0)
draw = ImageDraw.Draw(mask)
for row, line in enumerate(lines):
y = row * (char_h + line_gap)
for col, ch in enumerate(line):
if ch == ' ':
continue
x = col * char_w
draw.text((x, y), ch, font=font, fill=255)
return mask
img = Image.new('RGB', (W, H), BG)
draw = ImageDraw.Draw(img)
# 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)
TARGET_LOGO_W = 400
max_chars = max(len(line) for line in ASCII_ART)
_probe_font = load_font(MONO_FONT_CANDIDATES, 64)
_probe_cw, _ = mono_metrics(_probe_font)
font_size_logo = max(6, int(64 * TARGET_LOGO_W / (_probe_cw * max_chars)))
font_logo = load_font(MONO_FONT_CANDIDATES, font_size_logo)
char_w, char_h = mono_metrics(font_logo)
logo_mask = render_ascii_mask(font_logo, ASCII_ART, char_w, char_h, 2)
logo_w, logo_h = logo_mask.size
logo_x = (W - logo_w) // 2
logo_y = 380
sh_off = max(1, font_size_logo // 6)
shadow_mask = logo_mask.filter(ImageFilter.GaussianBlur(1))
img.paste(SHADOW, (logo_x + sh_off * 2, logo_y + sh_off * 2), shadow_mask)
img.paste(FG_DIM, (logo_x + sh_off, logo_y + sh_off), logo_mask)
img.paste(FG, (logo_x, logo_y), logo_mask)
font_sub = load_font(SUB_FONT_CANDIDATES, 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 + 48
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)
img = img.convert('RGB')
img.save('/usr/share/bee/wallpaper.png', optimize=True)
print('wallpaper written: /usr/share/bee/wallpaper.png')
PYEOF
echo "=== wallpaper done ==="

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@@ -5,6 +5,7 @@
# DCGM 4 is packaged per CUDA major. The image ships NVIDIA driver 590 with
# CUDA 13 userspace, so install the CUDA 13 build plus proprietary components
# explicitly.
nvidia-fabricmanager=%%NVIDIA_FABRICMANAGER_VERSION%%
datacenter-gpu-manager-4-cuda13=1:%%DCGM_VERSION%%
datacenter-gpu-manager-4-proprietary=1:%%DCGM_VERSION%%
datacenter-gpu-manager-4-proprietary-cuda13=1:%%DCGM_VERSION%%

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@@ -258,6 +258,22 @@ else
log "WARN: nvidia-smi not found — cannot enable persistence mode"
fi
# Start or refresh Fabric Manager after the NVIDIA stack is ready. On NVSwitch
# systems CUDA/DCGM can report "system not yet initialized" until fabric
# training completes under nvidia-fabricmanager.
if command -v systemctl >/dev/null 2>&1 && systemctl list-unit-files --no-legend 2>/dev/null | grep -q '^nvidia-fabricmanager\.service'; then
if systemctl restart nvidia-fabricmanager.service >/dev/null 2>&1; then
log "nvidia-fabricmanager restarted"
elif systemctl start nvidia-fabricmanager.service >/dev/null 2>&1; then
log "nvidia-fabricmanager started"
else
log "WARN: failed to start nvidia-fabricmanager.service"
systemctl status nvidia-fabricmanager.service --no-pager 2>&1 | sed 's/^/ fabricmanager: /' || true
fi
else
log "WARN: nvidia-fabricmanager.service not installed"
fi
# Start DCGM host engine so dcgmi can discover GPUs.
# nv-hostengine must run after the NVIDIA modules and device nodes are ready.
# If it started too early (for example via systemd before bee-nvidia-load), it can

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@@ -9,9 +9,9 @@ xset s noblank
# Set desktop background.
if [ -f /usr/share/bee/wallpaper.png ]; then
feh --bg-fill /usr/share/bee/wallpaper.png
feh --bg-center --image-bg '#000000' /usr/share/bee/wallpaper.png
else
xsetroot -solid '#f6c90e'
xsetroot -solid '#000000'
fi
tint2 &

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