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cs249r_book/mlsysim/CITATION.cff
2026-05-17 19:32:35 -04:00

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cff-version: 1.2.0
message: "If you use mlsysim in your research or teaching, please cite it as below."
title: "MLSys·im: First-Principles Infrastructure Modeling for Machine Learning Systems"
type: software
authors:
- family-names: "Janapa Reddi"
given-names: "Vijay"
orcid: "https://orcid.org/0000-0002-5005-2564"
affiliation: "Harvard University"
version: "0.1.2"
date-released: "2026-05-17"
license: "Apache-2.0"
url: "https://mlsysbook.ai/mlsysim"
repository-code: "https://github.com/harvard-edge/cs249r_book"
keywords:
- machine learning systems
- analytical modeling
- roofline model
- performance estimation
- ML infrastructure
- educational tool
abstract: >-
mlsysim is a first-principles analytical modeling framework for machine
learning systems, designed for education and early design-space reasoning
before empirical benchmarking. It encodes 22 fundamental constraints ("walls")
governing ML system performance into composable solvers, enabling quantitative
reasoning about hardware, communication, economics, and sustainability — from
sub-watt microcontrollers to exaflop-scale training clusters.