7b5fd91d3c
Run-01 was killed at step 19 by operator instruction to root-cause before spending a ~13.9h window. Two independent methods now agree on where the step time went, and neither was the hypothesis the consult panel converged on. Scaling fit (3 points, 2 params, residuals <3ms over an 8x range): A = 6.87e-4 s/token, B = 8.85e-8 s/token^2 quadratic share 20.9% @ w=2048 -> 67.8% @ w=16384 No fixed term was needed, which refutes launch-bound outright. Profiler kernel table (device rows only): attention 22,835.8 ms 65.2% fmha_cutlass*_sm80 dense GEMM 2,774.0 ms 7.9% other 5,739.0 ms 16.4% The attention kernels are sm80 — Ampere-generation CUTLASS running on an sm_120 Blackwell card, with the forward on the gmem fallback tier. That is the mechanism behind 100% SM utilisation at 27 of 304 available TFLOPS. Correctness cleared separately: the sliding mask asserts at max 1024 allowed/row, so the 25 windowed layers were genuinely windowed. The same probe found that right-padding is what pins the 5 global layers to an explicit 4D mask and off the is_causal fast path — measured at 9.4% slower for 24% less loss work at fixed width. The largest available win is not the attention kernel. The corpus is 29.9% padding, and bucket-to-pair + shuffle-to-mix takes it to 0.0% for >=35.5% wall clock, no new dependency, unchanged peak memory. Bucket size turned out not to be a diversity knob — roots per accumulation window are flat across a 256x range, so the global micro-batch shuffle does that work alone and the bucket should be tight. Adds docs/pfi/training-throughput-playbook.md as the durable model-agnostic home (sibling to the quantization playbook), the four probes under scripts/training-probes/ with raw output kept for re-derivation, and a §6 to the sizing doc carrying the Gemma-4-specific numbers and round-2 restart parameters. Measured negatives recorded so they are not re-chased: grouped_mm (0.9% slower, and MoE is only 7.9% of the step), CUDA graphs / torch.compile over the expert loop (no fixed cost to amortise), liger fused CE (~1-3% lever), FA4 on sm_120. Round-1 state preserved: 609MB encode cache, order manifest, truncation report, resume script. No checkpoints — it died at step 19 and the first was due at 100, so the lora_B inert-adapter gate never ran and moves to the restart.
docs/
Navigation map for the documentation tree. New session? Read
orientation.md first — it's the narrative overview
of the fleet, backup architecture, governing principles, and gotchas,
and it points at everything else.
Tree
docs/
├── orientation.md # start here — fleet overview + where-to-look guide
├── runbooks/ # ops runbooks (recovery, deployment phases)
│ ├── disaster-recovery.md
│ ├── nh3-prune-ritual.md
│ └── pbs-deployment.md
└── pfi/ # PFI-specific reference (services, models, VMs)
├── docker-stack.md
├── model-list.md
├── proxmox-vms.md
├── recommended-model-settings.md
├── vm-102-matrix-appservice.md
└── vm-102-matrix-synapse.md
What goes where
runbooks/— step-by-step ops procedures. Anything you'd reach for during an incident or while standing up new infrastructure. Examples: disaster recovery (blast-radius tiers + restoration steps), PBS deployment (9-phase rollout). New runbook → new file here.pfi/— PFI-specific reference material that's too narrow for the top-level CLAUDE.md but doesn't change incident response. AI model inventory, recommended inference settings, Matrix bridge config, Proxmox VM map. New stable reference → new file here.- Top-level (
docs/orientation.md,docs/README.md) — narrative guides about the workspace itself, not about specific infra.
Cross-references
- Fleet topology + servers table: top-level
CLAUDE.md. - Open work + recent milestones: top-level
STATUS.md. - Durable cross-session facts:
~/.claude/projects/-home-lkraven-development-eshpfi-management/memory/.
Conventions
- Markdown, GitHub-flavored. CommonMark renders fine in most viewers.
- File names are lowercase-kebab-case, descriptive. No dates in filenames — git history covers that.
- One topic per file. If a file grows past ~500 lines, look for a natural split before adding more.
- No checked-in binaries or checksums. Build/release artifacts belong
in a build pipeline or
tools/, notdocs/.