Cover Image

Tu(r)ning AI Green: Exploring Energy Efficiency Cascading with Orthogonal Optimizations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Rajput, Saurabhsingh, Saad, Mootez, Sharma, Tushar
Format:	Preprint
Published:	2025
Subjects:	Software Engineering Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

CodeGreen: Towards Improving Precision and Portability in Software Energy Measurement
by: Rajput, Saurabhsingh, et al.
Published: (2026)

Energy Flow Graph: Modeling Software Energy Consumption
by: Rajput, Saurabhsingh, et al.
Published: (2026)

COMET: Generating Commit Messages using Delta Graph Context Representation
by: Mandli, Abhinav Reddy, et al.
Published: (2024)

Smart but Costly? Benchmarking LLMs on Functional Accuracy and Energy Efficiency
by: Mehditabar, Mohammadjavad, et al.
Published: (2025)

A Validated Taxonomy on Software Energy Smells
by: Mehditabar, Mohammadjavad, et al.
Published: (2026)

Enhancing Energy-Awareness in Deep Learning through Fine-Grained Energy Measurement
by: Rajput, Saurabhsingh, et al.
Published: (2023)

FlipFlop: A Static Analysis-based Energy Optimization Framework for GPU Kernels
by: Rajput, Saurabhsingh, et al.
Published: (2026)

CONCORD: Towards a DSL for Configurable Graph Code Representation
by: Saad, Mootez, et al.
Published: (2024)

Why Attention Fails: A Taxonomy of Faults in Attention-Based Neural Networks
by: Jahan, Sigma, et al.
Published: (2025)

On the Effect of Token Merging on Pre-trained Models for Code
by: Saad, Mootez, et al.
Published: (2025)

Hierarchical Evaluation of Software Design Capabilities of Large Language Models of Code
by: Saad, Mootez, et al.
Published: (2025)

ALPINE: An adaptive language-agnostic pruning method for language models for code
by: Saad, Mootez, et al.
Published: (2024)

Towards Green AI: Decoding the Energy of LLM Inference in Software Development
by: Solovyeva, Lola, et al.
Published: (2026)

SENAI: Towards Software Engineering Native Generative Artificial Intelligence
by: Saad, Mootez, et al.
Published: (2025)

Correctness isnt Efficiency: Runtime Memory Divergence in LLM-Generated Code
by: Rajput, Prateek, et al.
Published: (2026)

Evaluating the Energy-Efficiency of the Code Generated by LLMs
by: Islam, Md Arman, et al.
Published: (2025)

Innovating for Tomorrow: The Convergence of SE and Green AI
by: Cruz, Luís, et al.
Published: (2024)

On Inter-dataset Code Duplication and Data Leakage in Large Language Models
by: López, José Antonio Hernández, et al.
Published: (2024)

Greening AI-enabled Systems with Software Engineering: A Research Agenda for Environmentally Sustainable AI Practices
by: Cruz, Luís, et al.
Published: (2025)

SWEnergy: An Empirical Study on Energy Efficiency in Agentic Issue Resolution Frameworks with SLMs
by: Tripathy, Arihant, et al.
Published: (2025)

A Controlled Experiment on the Energy Efficiency of the Source Code Generated by Code Llama
by: Cursaru, Vlad-Andrei, et al.
Published: (2024)

Do Generative AI Tools Ensure Green Code? An Investigative Study
by: Sikand, Samarth, et al.
Published: (2025)

FasterPy: An LLM-based Code Execution Efficiency Optimization Framework
by: Wu, Yue, et al.
Published: (2025)

Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization
by: Du, Mingzhe, et al.
Published: (2025)

Sustainable Machine Learning Retraining: Optimizing Energy Efficiency Without Compromising Accuracy
by: Poenaru-Olaru, Lorena, et al.
Published: (2025)

Exploring the Challenges and Opportunities of AI-assisted Codebase Generation
by: Eibl, Philipp, et al.
Published: (2025)

WhatsCode: Large-Scale GenAI Deployment for Developer Efficiency at WhatsApp
by: Mao, Ke, et al.
Published: (2025)

From User Interface to Agent Interface: Efficiency Optimization of UI Representations for LLM Agents
by: Ran, Dezhi, et al.
Published: (2025)

Past, Present and Future: Exploring Adaptive AI in Software Development Bots
by: Elsisi, Omar, et al.
Published: (2025)

DevLicOps: A Framework for Mitigating Licensing Risks in AI-Generated Code
by: Sharma, Pratyush Nidhi, et al.
Published: (2025)

Case Study: Leveraging GenAI to Build AI-based Surrogates and Regressors for Modeling Radio Frequency Heating in Fusion Energy Science
by: Bethel, E. Wes, et al.
Published: (2024)

Beyond Inference-Only Deployment: Comparing Weight-Based Consolidation Against Cascading Compaction
by: Dennis, Simon, et al.
Published: (2026)

MEMRES: A Memory-Augmented Resolver with Confidence Cascade for Agentic Python Dependency Resolution
by: Minh, Dao Sy Duy, et al.
Published: (2026)

Research on Efficiency Analysis of Microservices
by: Chen, Abel C. H.
Published: (2023)

Decentralised Governance-Driven Architecture for Designing Foundation Model based Systems: Exploring the Role of Blockchain in Responsible AI
by: Liu, Yue, et al.
Published: (2023)

Patched MOA: optimizing inference for diverse software development tasks
by: Sharma, Asankhaya
Published: (2024)

Patched RTC: evaluating LLMs for diverse software development tasks
by: Sharma, Asankhaya
Published: (2024)

Energy-Aware Code Generation with LLMs: Benchmarking Small vs. Large Language Models for Sustainable AI Programming
by: Ashraf, Humza, et al.
Published: (2025)

Dissecting Transformers: A CLEAR Perspective towards Green AI
by: Jain, Hemang, et al.
Published: (2025)

Towards Better Correctness and Efficiency in Code Generation
by: Feng, Yunlong, et al.
Published: (2025)