Files
esh-pfi-infrastructure/docs
vh 7b5fd91d3c docs(gemma4-erp-tune): root-cause the 8.6% MFU — attention on Ampere kernels, 29.9% padding
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.
2026-08-24 22:10:51 -07:00
..

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/, not docs/.