Carbon-Aware Computing

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20 papers2 papers in the last four weeks, down 33% on the four weeks before. 0.0% of all new papers.

Dissecting the Carbon-SLO Tension in Geo-Distributed LLM Serving
Oct 10, 2026Burak Topcu, Musa Cim, Zuhal Ozturk +1LLM Inference Scheduling Carbon-Aware Computing
Department of Computer Science and Engineering, The Pennsylvania State University, State College, PA 16801, USA
Beyond Energy: When Sustainability Dimensions Reshape LLM Serving Decisions
Sep 28, 2026Tianyao Shi, Xipeng Shen, Yi DingLLM Inference Efficiency LLM Serving
Elmore Family School of Electrical and Computer Engineering, Purdue University, USA
A Game-Theoretic Framework for Incentive-Compatible AI training Under Renewable-Energy Constraints
Sep 14, 2026Konstantinos Varsos, Ramin Khalili, Adamantia Stamou +2Mechanism Design Energy-Efficient ML
Athens University of Economics and Business, Greece · Independent researcher, Munich Germany
Carbon-Aware Routing for Function Calling in Edge-Cloud LLM Systems
Sep 11, 2026Aikaterini Maria Panteleaki, Varatheepan Paramanayakam, Spyros Tragoudas +1LLM Routing Carbon-Aware Computing
School of Electrical, Computer and Biomedical Engineering Southern Illinois University Carbondale
Toward Sustainable Distributed LLM Inference: A Systems Synthesis and Research Agenda for an Energy-, Carbon-, and Cache-Aware llm-d Control Plane
Sep 3, 2026Twinkll SisodiaEnergy-Aware LLM Inference LLM Inference
AgentDecarbonizer: Carbon-Aware Execution for AI Agents
Aug 20, 2026Leyi Yan, Shuangning Li, Sihang LiuCarbon-Aware Computing LLM Agent Workflow Optimization
University of Waterloo, Canada · University of Chicago, USA
InFactPlanner: Planning Sustainable Geo-Distributed LLM Data Centers
Aug 13, 2026Nicoletta Tsiopani, Moysis Symeonides, George Pallis +1Energy-Efficient ML LLM Inference Serving
Department of Computer Science University of Cyprus
Can We Optimize the Performance-Carbon Emission Break-Even Point?: The Quest for Greener LLMs
Aug 9, 2026Sourav Das, Tanmay Joshi, Kripabandhu GhoshFine-Tuning LLM Fine-Tuning
IIIT Kalyani · BITS Pilani Goa · IISER Kolkata
Hierarchical Multi-Agent Reinforcement Learning for Carbon-Aware AI Data Centers in Power Distribution Systems
Jul 3, 2026Hyunsoo Lee, Panggah Prabawa, Dae-Hyun Choi +1Energy-Efficient ML Data Center Energy Management
LG Electronics, 17709, Pyeongtaek, Gyeonggi-do, Republic of Korea · School of Electrical and Electronics Engineering, Chung-Ang University, Seoul 06974, Republic of Korea · Department of Electrical and Computer Engineering, Korea University, Seoul 02841, Republic of Korea
Power-Flexible AI Data Centers: A New Paradigm for Grid-Responsive Compute
Jun 23, 2026Chris Williams, Philip Colangelo, Ayse Coskun +15Demand Response Carbon-Aware Computing
Emerald AI · Electric Power Research Institute (EPRI) · National Grid +2
Green SARC: Predictive Cost and Carbon Governance for Agentic AI Systems
Jun 14, 2026Gaston BesansonEnergy-Efficient ML Cost-Aware Inference
Universidad Torcuato Di Tella
GAR: Carbon-Aware Routing for LLM Inference via Constrained Optimization
May 12, 2026Disha Sheshanarayana, Rajat Subhra Pal, Manjira Sinha +1LLM Inference Efficiency Constrained Optimization
Manipal University Jaipur · TCS Research
FM-CAC: Carbon-Aware Control for Battery-Buffered Edge AI via Time-Series Foundation Models
Apr 7, 2026Kang Yang, Walid A. Hanafy, Prashant Shenoy +1Carbon-Aware Computing Energy-Efficient ML
University of California, Los Angeles Los Angeles, USA · University of Massachusetts Amherst Amherst, USA
Green AI Carbon Optimizer: Carbon-Efficient Training Location Recommendation and Global AI Energy Demand Forecasting
Apr 6, 2026Yuxin Chen, Hao Gao, Chujie ZouEnergy-Efficient ML Carbon-Aware Computing
University of Helsinki, Finland · Independent Researcher
CARGO: Carbon-Aware Gossip Orchestration in Smart Shipping
Mar 29, 2026Alexandros S. Kalafatelis, Nikolaos Nomikos, Vasileios Nikolakakis +2Carbon-Aware Computing Federated Learning
Department of Ports Management and Shipping, National and Kapodistrian University of Athens, 34400 Euboea, Greece · Laskaridis Shipping Co. Ltd, 14562, Kifisia Greece
COMPASS: The explainable agentic framework for Sovereignty, Sustainability, Compliance, and Ethics
Mar 11, 2026Jean-Sébastien Dessureault, Alain-Thierry Iliho Manzi, Soukaina Alaoui Ismaili +3Carbon-Aware Computing AI Agent Governance
Mathematics and Computer science, Université du Québec à Trois-Rivières, 3351 Boul. des Forges, Trois-Rivières, G8Z 4M3, Québec, Canada. · LSSI - Laboratory of Signal and System Integration, Electrical and Computer Engineering Department, Université du Québec à Trois-Rivières, 3351 Boul. des Forges, Trois-Rivières, G8Z 4M3, Québec, Canada. · Social Communication Department, Université du Québec à Trois-Rivières, 3351 Boul. des Forges, Trois-Rivières, G8Z 4M3, Québec, Canada. +1
Green or Fast? Learning to Balance Cold Starts and Idle Carbon in Serverless Computing
Feb 27, 2026Bowen Sun, Christos D. Antonopoulos, Evgenia Smirni +3Cloud Computing Carbon-Aware Computing
Department of Computer Science, William & Mary, Williamsburg, VA, USA · Department of Computer Science, University of Thessaly, Volos, Greece
Carbon-Aware Governance Gates: An Architecture for Sustainable GenAI Development
Feb 23, 2026Mateen A. Abbasi, Tommi J. Mikkonen, Petri J. Ihantola +3Carbon-Aware Computing AI Governance
University of Jyväskylä, Jyväskylä, Finland · Tampere University, Tampere, Finland
Carbon-aware decentralized dynamic task offloading in MIMO-MEC networks via multi-agent reinforcement learning
Feb 21, 2026Mubshra Zulfiqar, Muhammad Ayzed Mirza, Basit QureshiComputation Offloading Carbon-Aware Computing
School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, 430000, Hubei, China · School of Computer Science and Information Engineering, Qilu Institute of Technology, Jinan, 250200, Shandong, China · Department of Computer Science, Prince Sultan University, Riyadh, 12435, Riyadh Province, Saudi Arabia
AI-CARE: Carbon-Aware Reporting Evaluation Metric for AI Models
Feb 17, 2026KC Santosh, Srikanth Baride, Rodrigue RizkCarbon-Aware Computing Energy-Efficient ML
USD Artificial Intelligence Research, Department of Computer Science University of South Dakota Vermillion, SD 57069, USA

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Dissecting the Carbon-SLO Tension in Geo-Distributed LLM Serving

Burak Topcu, Musa Cim, Zuhal Ozturk, Mahmut Taylan Kandemir

Department of Computer Science and Engineering, The Pennsylvania State University, State College, PA 16801, USA

LLM Inference Scheduling Carbon-Aware Computing LLM Inference Serving

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Large Language Model (LLM) inference is driving a growing share of datacenter carbon emissions. Although carbon-aware scheduling can reduce these emissions in geo-distributed datacenters by exploiting the spatiotemporal variations in grid carbon intensity, the latency-sensitive nature of LLM serving constrains this design space. While prior studies investigate the carbon savings achievable through spatial scheduling, they oversimplify the dynamics of modern inference engines, such as queueing and continuous batching, which strongly shape inference latency. We address this issue by designing and evaluating a latency-centric, geo-distributed inference simulator, calibrated with hardware-grounded latency and power measurements, that reproduces these dynamics and enables the study of carbon savings under strict service-level objectives (SLOs). We then formulate a series of SLO- and carbon-aware schedulers of increasing sophistication, from per-request heuristics to batch-level optimization: (i) a greedy heuristic, (ii) an integer linear programming (ILP)-based scheduler jointly assigning batches of requests, (iii) an iterative ILP-based solution projecting its own assignments back into the load estimates to capture load coupling, and (iv) a facility mixed-integer linear programming (MILP) scheduler pricing the energy of batched requests collectively rather than in isolation. Across three LLMs under MLPerf SLOs and varying system loads, the MILP-based option offers the best carbon-SLO balance, reducing carbon emissions by up to 60% relative to the round-robin policy, with an average SLO violation of 3%. Our characterization further shows that savings grow with the spread of carbon intensity across datacenters and shrink as system load increases, while SLO attainment depends on how frequently schedulers receive datacenters' load updates.