TTNN Ops Coverage Matrix

An interactive, zero-dependency dashboard for the TTNN (Tenstorrent) operation test matrix — visualizing how 259 operations behave across every dtype × layout × memory configuration.

Built to deploy as a Cloudflare Workers Static Assets site. The entire front end is hand-rolled HTML/CSS/SVG with no runtime libraries, so it loads instantly and works fully offline.

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What it shows

The source data (ops.csv) is a sweep of 6,124 test configurations — each of 259 ops run across 6 dtypes × 2 layouts × 2 memory configs. Each run's raw pcc_or_reason column is classified into a clean 6-status taxonomy:

Status	Meaning
🟢 Pass	Output matched the golden reference within PCC threshold
🟠 PCC Fail	Ran, but numerically inaccurate (PCC below threshold / NaN)
🔴 Hard Error	TT_FATAL / TT_THROW — crashed before producing a result
🔵 No Golden	Ran, but no reference output to verify against
⚪ Skipped	Config unsupported / intentionally skipped
◾ Not in TTNN	Operation not implemented

Dashboard panels

• KPI cards — pass rate, hard errors, PCC failures, no-golden count, op total, config total
• Result-distribution donut — click any slice to solo that status across the table
• Outcome by axis — stacked pass/fail composition per dtype, layout, and memory
• Top hard-error signatures — the most common device assertions, grouped by source_file:line
• Coverage snapshot — how configs split between verifiable and unverifiable
• Operation leaderboard — every op, sortable by any column, searchable. Click a row to expand a dtype × layout·mem heatmap; hover any cell for the exact failure reason.

Keyboard: / focuses search · Esc clears search/solo.

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Project layout

.
├── public/            # ← deployed to Cloudflare (static assets)
│   ├── index.html     #   markup + design system (CSS)
│   ├── app.js         #   chart/table renderer (no deps)
│   └── data.js        #   generated — window.DASH payload
├── ops.csv            # source data (regenerate data.js from this)
├── process.py         # CSV → public/data.js transformer + classifier
├── wrangler.jsonc     # Cloudflare Workers static-assets config
└── package.json

public/data.js is a build artifact — it is not committed. CI regenerates it from ops.csv on every deploy (and you regenerate it locally with python3 process.py). ops.csv is the single source of truth.

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Local development

# Regenerate the dashboard data from the CSV
python3 process.py            # → writes public/data.js

# Serve locally (any static server works)
npm run serve                 # http://localhost:8080  (binds 0.0.0.0)
#   or
npx wrangler dev              # http://localhost:8787  (emulates the edge)

Updating the data is just: replace ops.csv → run python3 process.py → refresh. No rebuild step for HTML/JS.

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Deploy to Cloudflare Workers

This repo is configured for Workers Static Assets (no Worker script — Cloudflare serves public/ directly from the edge).

npm install          # pulls wrangler
npx wrangler login   # one-time, opens browser
npm run deploy       # = python3 process.py && wrangler deploy

After the first deploy it's live at:

https://ttnn-ops-coverage.<your-subdomain>.workers.dev

Custom domain: https://ttnn-ops-coverage.aswincloud.com/

Auto-deploy on push

This repo is connected to Cloudflare Workers Builds (CF-native Git integration — configured in the Cloudflare dashboard, nothing required in the repo itself). On every push to main, Cloudflare runs:

Step	Command
Build	npm run build → python3 process.py rebuilds public/data.js from ops.csv
Deploy	npx wrangler deploy → ships public/ to the edge

So updating the dashboard is just: replace ops.csv, commit, push → live in ~a minute. Because the build regenerates data.js, ops.csv is the only file you ever need to touch.

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Regenerating data.js

process.py does all the heavy lifting:

1. Parses ops.csv (RFC-correct CSV — failure reasons contain embedded commas/newlines from C++ backtraces).
2. Classifies each row's accepted + pcc_or_reason into the 6-status taxonomy.
3. Collapses verbose TT_FATAL/TT_THROW backtraces into KIND file:line — message signatures and groups them.
4. Computes per-op, per-dtype, per-layout, per-memory aggregations.
5. Emits a compact window.DASH = {…} payload (~136 KB) to public/data.js.

Totals always reconcile to the row count — the script prints a status breakdown on every run.