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calculator: production hardening — drop private repo/live links, keep author attribution
Publication-format pass for the public aws-samples PR (god-mode 3-LLM reviewed): - Remove the private github.com/dmvevents + dmvevents.github.io Source/live links from every file header (.py/.html/.md) and the DEPLOYMENT-GUIDE companion-repo link — they 404 for customers. Kept 'Author: Anton Alexander' (the maintainer's actual ask). - Reworded the companion-harness reference to describe the methodology, not a non-public artifact a reader is told to run. - Confirmed: no SPDX/copyright header added (matches sibling nemotron/ultra, which carries none — inherits repo-root Apache-2.0); ledger.jsonl has no internal refs; no committed __pycache__/.pyc; .gitignore covers it. Verified: calc.py --selftest green standalone, both HTML pages parse, 0 private refs.
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Container-Root/eks/deployment/inference/agentic-ai/disagg-calculator/analyze/calc.py

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#!/usr/bin/env python3
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"""
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Author: Anton Alexander
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Source: github.com/dmvevents/dynamo-disagg-optimizer · live: dmvevents.github.io/dynamo-disagg-optimizer/calculator.html
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DISCLAIMER: Provided free, as a utility, for estimation and planning ONLY. AWS and the authors make no
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warranty or guarantee of model performance and accept no liability for results obtained from its use.

Container-Root/eks/deployment/inference/agentic-ai/disagg-calculator/analyze/calibration.py

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#!/usr/bin/env python3
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"""
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Author: Anton Alexander
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Source: github.com/dmvevents/dynamo-disagg-optimizer · live: dmvevents.github.io/dynamo-disagg-optimizer/calculator.html
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calibration.py — close the loop: PREDICT → MEASURE → DELTA → CORRECTION-FACTOR, refined over time.
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Container-Root/eks/deployment/inference/agentic-ai/disagg-calculator/docs/DEPLOYMENT-GUIDE.md

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# Deployment guide: aggregation vs disaggregation, end-to-end
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*Author: Anton Alexander*
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*Source: github.com/dmvevents/dynamo-disagg-optimizer · live: dmvevents.github.io/dynamo-disagg-optimizer/calculator.html*
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A decision-then-deploy runbook. You start with a model + an SLA + a budget, and finish with a deployed,
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> `calibration.py`) and the two browser pages — the cheap, run-anywhere screening tool. This runbook also
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> references the optional **live-sweep harness** (`driver/sweep.py`, `driver/goodput.py`, `cost.py`,
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> `render_charts.py`) and the L3 GPU benchmarking steps; those are the deeper research layer and live in the
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> companion project ([github.com/dmvevents/dynamo-disagg-optimizer](https://github.com/dmvevents/dynamo-disagg-optimizer)).
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> companion research harness (not required to use the calculator).
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> You do **not** need them to use the calculator — they're how the calculator gets calibrated against real
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> GPUs. Steps 0, 2 (L0), and 7 are self-contained here; steps 1, 3–6 point at the companion harness or
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> upstream tooling.

Container-Root/eks/deployment/inference/agentic-ai/disagg-calculator/docs/METHODOLOGY.md

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# Methodology: deciding aggregation vs disaggregation, and finding the optimal settings — for ANY model on ANY compute
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*Author: Anton Alexander*
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*Source: github.com/dmvevents/dynamo-disagg-optimizer · live: dmvevents.github.io/dynamo-disagg-optimizer/calculator.html*
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A **repeatable, model-agnostic, hardware-agnostic, engine-agnostic** process. Plug in a model (its HF

Container-Root/eks/deployment/inference/agentic-ai/disagg-calculator/web/calculator.html

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<!DOCTYPE html>
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<!-- Author: Anton Alexander | Source: github.com/dmvevents/dynamo-disagg-optimizer · live: dmvevents.github.io/dynamo-disagg-optimizer/calculator.html -->
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<!-- Author: Anton Alexander -->
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<html lang="en">
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<head>
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<meta charset="utf-8"/>

Container-Root/eks/deployment/inference/agentic-ai/disagg-calculator/web/index.html

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<!DOCTYPE html>
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<!-- Author: Anton Alexander | Source: github.com/dmvevents/dynamo-disagg-optimizer · live: dmvevents.github.io/dynamo-disagg-optimizer/calculator.html -->
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<!-- Author: Anton Alexander -->
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<html lang="en">
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<head>
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<meta charset="utf-8"/>

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