Cover Image

Greener Deep Reinforcement Learning: Analysis of Energy and Carbon Efficiency Across Atari Benchmarks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gardner, Jason, Dutta, Ayan, Roy, Swapnoneel, Kreidl, O. Patrick, Boloni, Ladislau
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Performance
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Bounomodes: the grazing ox algorithm for exploration of clustered anomalies
by: Matloob, Samuel, et al.
Published: (2025)

Offline Reinforcement-Learning-Based Power Control for Application-Agnostic Energy Efficiency
by: Raj, Akhilesh, et al.
Published: (2026)

Tabular and Deep Reinforcement Learning for Gittins Index
by: Dhankhar, Harshit, et al.
Published: (2024)

oneDNN Graph Compiler: A Hybrid Approach for High-Performance Deep Learning Compilation
by: Li, Jianhui, et al.
Published: (2023)

ALERT: Accurate Learning for Energy and Timeliness
by: Wan, Chengcheng, et al.
Published: (2019)

Memory Analysis on the Training Course of DeepSeek Models
by: Zhang, Ping, et al.
Published: (2025)

Anatomizing Deep Learning Inference in Web Browsers
by: Wang, Qipeng, et al.
Published: (2024)

Efficient Reinforcement Learning for Routing Jobs in Heterogeneous Queueing Systems
by: Jali, Neharika, et al.
Published: (2024)

Forecasting GPU Performance for Deep Learning Training and Inference
by: Lee, Seonho, et al.
Published: (2024)

Towards Computational Performance Engineering for Unsupervised Concept Drift Detection -- Complexities, Benchmarking, Performance Analysis
by: Werner, Elias, et al.
Published: (2023)

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

Benchmarking GPUs on SVBRDF Extractor Model
by: Kandel, Narayan, et al.
Published: (2023)

Cloud Computing Energy Consumption Prediction Based on Kernel Extreme Learning Machine Algorithm Improved by Vector Weighted Average Algorithm
by: Wang, Yuqing, et al.
Published: (2025)

CEBench: A Benchmarking Toolkit for the Cost-Effectiveness of LLM Pipelines
by: Sun, Wenbo, et al.
Published: (2024)

DeepSpeed-FastGen: High-throughput Text Generation for LLMs via MII and DeepSpeed-Inference
by: Holmes, Connor, et al.
Published: (2024)

Single-Thread JPEG Decoder Benchmarks Mis-Evaluate ML Data Loaders
by: Iglovikov, Vladimir, et al.
Published: (2026)

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels
by: Wang, Han, et al.
Published: (2026)

Unveiling Energy Efficiency in Deep Learning: Measurement, Prediction, and Scoring across Edge Devices
by: Tu, Xiaolong, et al.
Published: (2023)

EARL: Energy-Aware Optimization of Liquid State Machines for Pervasive AI
by: Iqbal, Zain, et al.
Published: (2026)

Towards Generalizable Generic Harmful Speech Datasets for Implicit Hate Speech Detection
by: Almohaimeed, Saad, et al.
Published: (2025)

Model-Based Reinforcement Learning for Atari
by: Kaiser, Lukasz, et al.
Published: (2019)

Automating Energy-Efficient GPU Kernel Generation: A Fast Search-Based Compilation Approach
by: Zhang, Yijia, et al.
Published: (2024)

GreenServ: Energy-Efficient Context-Aware Dynamic Routing for Multi-Model LLM Inference
by: Ziller, Thomas, et al.
Published: (2026)

Intelligent Green Efficiency for Intrusion Detection
by: Pereira, Pedro, et al.
Published: (2024)

Biases in Edge Language Models: Detection, Analysis, and Mitigation
by: Sharma, Vinamra, et al.
Published: (2025)

The Race to Efficiency: A New Perspective on AI Scaling Laws
by: Lu, Chien-Ping
Published: (2025)

HackAtari: Atari Learning Environments for Robust and Continual Reinforcement Learning
by: Delfosse, Quentin, et al.
Published: (2024)

A Structure-Aware Framework for Learning Device Placements on Computation Graphs
by: Duan, Shukai, et al.
Published: (2024)

MIREncoder: Multi-modal IR-based Pretrained Embeddings for Performance Optimizations
by: Dutta, Akash, et al.
Published: (2024)

Catastrophic Cyber Capabilities Benchmark (3CB): Robustly Evaluating LLM Agent Cyber Offense Capabilities
by: Anurin, Andrey, et al.
Published: (2024)

PrETi: Predicting Execution Time in Early Stage with LLVM and Machine Learning
by: Xu, Risheng, et al.
Published: (2025)

PixelBrax: Learning Continuous Control from Pixels End-to-End on the GPU
by: McInroe, Trevor, et al.
Published: (2025)

Machine Learning Methods for Evaluating Public Crisis: Meta-Analysis
by: Okpala, Izunna, et al.
Published: (2023)

Democratizing AI: A Comparative Study in Deep Learning Efficiency and Future Trends in Computational Processing
by: Amin, Lisan Al, et al.
Published: (2026)

Energy per Successful Goal: Goal-Level Energy Accounting for Agentic AI Systems
by: Panigrahy, Deepak, et al.
Published: (2026)

DeepGD: A Multi-Objective Black-Box Test Selection Approach for Deep Neural Networks
by: Aghababaeyan, Zohreh, et al.
Published: (2023)

Profiling LoRA/QLoRA Fine-Tuning Efficiency on Consumer GPUs: An RTX 4060 Case Study
by: Avinash, MSR
Published: (2025)

Machine Learning Models for Reinforced Concrete Pipes Condition Prediction: The State-of-the-Art Using Artificial Neural Networks and Multiple Linear Regression in a Wisconsin Case Study
by: Mohammadagha, Mohsen, et al.
Published: (2025)

RooflineBench: A Benchmarking Framework for On-Device LLMs via Roofline Analysis
by: Bi, Zhen, et al.
Published: (2026)

Research on Low-Latency Inference and Training Efficiency Optimization for Graph Neural Network and Large Language Model-Based Recommendation Systems
by: Zhao, Yushang, et al.
Published: (2025)