<!doctype html><!-- This site was created with Wowchemy. https://www.wowchemy.com --><!-- Last Published: May 23, 2025 --><html lang=en-us><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=generator content="Wowchemy 5.7.0 for Hugo"><link rel=preconnect href=https://fonts.gstatic.com crossorigin><link rel=preload as=style href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap"><link rel=stylesheet href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap" media=print onload='this.media="all"'><link rel=stylesheet href=/css/vendor-bundle.min.16f785cdb553c8c4431db6775122af35.css media=print onload='this.media="all"'><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/academicons@1.9.2/css/academicons.min.css integrity="sha512-KlJCpRsLf+KKu2VQa5vmRuClRFjxc5lXO03ixZt82HZUk41+1I0bD8KBSA0fY290ayMfWYI9udIqeOWSu1/uZg==" crossorigin=anonymous media=print onload='this.media="all"'><link rel=stylesheet href=/css/wowchemy.1e91b7483bedea3afd020221b44e71d4.css><link rel=stylesheet href=/css/libs/chroma/github-light.min.css title=hl-light media=print onload='this.media="all"'><link rel=stylesheet href=/css/libs/chroma/dracula.min.css title=hl-dark media=print onload='this.media="all"' disabled><meta name=author content="Vivek Anand"><meta name=description content="We study the problem of scheduling precedence-constrained tasks to balance between performance and energy consumption. We consider a system with multiple servers capable of speed scaling and seek to schedule precedence-constrained tasks to minimize a linear combination of performance and energy consumption. Inspired by the single-server setting, we propose the concept of pseudo-size for individual tasks, which is a measure of the externalities of a task in the precedence graph and is learned from historical workload data.We then propose a two-stage scheduling framework that uses a learned pseudo-size approximation and achieves a provable approximation bound on the linear combination of performance and energy consumption for both makespan and total weighted completion time, where the quality of the bound depends on the approximation quality of pseudo-sizes. We show experimentally that learning-based approaches consistently perform near optimally."><link rel=alternate hreflang=en-us href=https://the-vivek.netlify.app/www.dl.acm.org/doi/pdf/10.1145/3680278><link rel=canonical href=https://the-vivek.netlify.app/www.dl.acm.org/doi/pdf/10.1145/3680278><link rel=manifest href=/manifest.webmanifest><link rel=icon type=image/png href=/media/icon_hucedc9910d4570ef2320a38d627251239_116407_32x32_fill_lanczos_center_3.png><link rel=apple-touch-icon type=image/png href=/media/icon_hucedc9910d4570ef2320a38d627251239_116407_180x180_fill_lanczos_center_3.png><meta name=theme-color content="#3f51b5"><meta property="twitter:card" content="summary"><meta property="twitter:site" content="@wowchemy"><meta property="twitter:creator" content="@wowchemy"><meta property="twitter:image" content="https://the-vivek.netlify.app/media/icon_hucedc9910d4570ef2320a38d627251239_116407_512x512_fill_lanczos_center_3.png"><meta property="og:site_name" content="Vivek Anand"><meta property="og:url" content="https://the-vivek.netlify.app/www.dl.acm.org/doi/pdf/10.1145/3680278"><meta property="og:title" content="Learning-Augmented Energy-Aware List Scheduling of Precedence-Constrained Tasks | Vivek Anand"><meta property="og:description" content="We study the problem of scheduling precedence-constrained tasks to balance between performance and energy consumption. We consider a system with multiple servers capable of speed scaling and seek to schedule precedence-constrained tasks to minimize a linear combination of performance and energy consumption. Inspired by the single-server setting, we propose the concept of pseudo-size for individual tasks, which is a measure of the externalities of a task in the precedence graph and is learned from historical workload data.We then propose a two-stage scheduling framework that uses a learned pseudo-size approximation and achieves a provable approximation bound on the linear combination of performance and energy consumption for both makespan and total weighted completion time, where the quality of the bound depends on the approximation quality of pseudo-sizes. We show experimentally that learning-based approaches consistently perform near optimally."><meta property="og:image" content="https://the-vivek.netlify.app/media/icon_hucedc9910d4570ef2320a38d627251239_116407_512x512_fill_lanczos_center_3.png"><meta property="og:locale" content="en-us"><meta property="article:published_time" content="2024-01-01T00:00:00+00:00"><meta property="article:modified_time" content="2025-05-23T18:29:03-04:00"><script type=application/ld+json>{"@context":"https://schema.org","@type":"Article","mainEntityOfPage":{"@type":"WebPage","@id":"https://the-vivek.netlify.app/www.dl.acm.org/doi/pdf/10.1145/3680278"},"headline":"Learning-Augmented Energy-Aware List Scheduling of Precedence-Constrained Tasks","datePublished":"2024-01-01T00:00:00Z","dateModified":"2025-05-23T18:29:03-04:00","author":{"@type":"Person","name":"Yu Su"},"publisher":{"@type":"Organization","name":"Vivek Anand","logo":{"@type":"ImageObject","url":"https://the-vivek.netlify.app/media/icon_hucedc9910d4570ef2320a38d627251239_116407_192x192_fill_lanczos_center_3.png"}},"description":"We study the problem of scheduling precedence-constrained tasks to balance between performance and energy consumption. We consider a system with multiple servers capable of speed scaling and seek to schedule precedence-constrained tasks to minimize a linear combination of performance and energy consumption. Inspired by the single-server setting, we propose the concept of pseudo-size for individual tasks, which is a measure of the externalities of a task in the precedence graph and is learned from historical workload data.We then propose a two-stage scheduling framework that uses a learned pseudo-size approximation and achieves a provable approximation bound on the linear combination of performance and energy consumption for both makespan and total weighted completion time, where the quality of the bound depends on the approximation quality of pseudo-sizes. We show experimentally that learning-based approaches consistently perform near optimally."}</script><title>Learning-Augmented Energy-Aware List Scheduling of Precedence-Constrained Tasks | Vivek Anand</title></head><body id=top data-spy=scroll data-offset=70 data-target=#TableOfContents class=page-wrapper data-wc-page-id=afdc90e5c3c4c3a4470189947f1fa107><script src=/js/wowchemy-init.min.ba7a0b5301d7bddff935a3260b04e001.js></script><aside class=search-modal id=search><div class=container><section class=search-header><div class="row no-gutters justify-content-between mb-3"><div class=col-6><h1>Search</h1></div><div class="col-6 col-search-close"><a class=js-search href=# aria-label=Close><i class="fas fa-times-circle text-muted" aria-hidden=true></i></a></div></div><div id=search-box><input name=q id=search-query placeholder=Search... autocapitalize=off autocomplete=off autocorrect=off spellcheck=false type=search class=form-control aria-label=Search...></div></section><section class=section-search-results><div id=search-hits></div></section></div></aside><div class="page-header header--fixed"><header><nav class="navbar navbar-expand-lg navbar-light compensate-for-scrollbar" id=navbar-main><div class=container-xl><div class="d-none d-lg-inline-flex"><a class=navbar-brand href=/>Vivek Anand</a></div><button type=button class=navbar-toggler data-toggle=collapse data-target=#navbar-content aria-controls=navbar-content aria-expanded=false aria-label="Toggle navigation">
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<a href=# class="dropdown-item js-set-theme-auto"><span>Automatic</span></a></div></li></ul></div></nav></header></div><div class=page-body><div class=pub><div class="article-container pt-3"><h1>Learning-Augmented Energy-Aware List Scheduling of Precedence-Constrained Tasks</h1><div class=article-metadata><div><span>Yu Su</span>, <span>Vivek Anand</span>, <span>Jannie Yu</span>, <span>Jian Tan</span>, <span>Adam Wierman</span></div><span class=article-date>January, 2024</span></div><div class="btn-links mb-3"><a class="btn btn-outline-primary btn-page-header" href=//www.dl.acm.org/doi/pdf/10.1145/3680278 target=_blank rel=noopener>PDF</a>
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