Cover Image

EnergyLens: Predictive Energy-Aware Exploration for Multi-GPU LLM Inference Optimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Song, Zhiye, Lee, Kyungmi, Lee, Eun Kyung, Zhang, Xin, Eilam, Tamar, Chandrakasan, Anantha P.
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

EnergAIzer: Fast and Accurate GPU Power Estimation Framework for AI Workloads
by: Lee, Kyungmi, et al.
Published: (2026)

EnergyLens: Interpretable Closed-Form Energy Models for Multimodal LLM Inference Serving
by: Palladino, Vittorio, et al.
Published: (2026)

LEDRO: LLM-Enhanced Design Space Reduction and Optimization for Analog Circuits
by: Kochar, Dimple Vijay, et al.
Published: (2024)

A Robust Power Model Training Framework for Cloud Native Runtime Energy Metric Exporter
by: Choochotkaew, Sunyanan, et al.
Published: (2024)

Mind the Memory Gap: Unveiling GPU Bottlenecks in Large-Batch LLM Inference
by: Recasens, Pol G., et al.
Published: (2025)

FedCore: Straggler-Free Federated Learning with Distributed Coresets
by: Guo, Hongpeng, et al.
Published: (2024)

Characterizing LLM Inference Energy-Performance Tradeoffs across Workloads and GPU Scaling
by: Maliakel, Paul Joe, et al.
Published: (2025)

Online GPU Energy Optimization with Switching-Aware Bandits
by: Xu, Xiongxiao, et al.
Published: (2024)

SLO-aware GPU Frequency Scaling for Energy Efficient LLM Inference Serving
by: Kakolyris, Andreas Kosmas, et al.
Published: (2024)

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

Multi-LLM Adaptive Conformal Inference for Reliable LLM Responses
by: Noh, Kangjun, et al.
Published: (2026)

AGFT: An Adaptive GPU Frequency Tuner for Real-Time LLM Inference Optimization
by: Ye, Zicong, et al.
Published: (2025)

Adaptive Block-Scaled Data Types
by: Cook, Jack, et al.
Published: (2026)

IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection
by: Ramakrishnan, Aashish Anantha, et al.
Published: (2025)

LLM-Guided Runtime Parameter Optimization for Energy-Efficient Model Inference
by: Crumpacker, Katelyn, et al.
Published: (2026)

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

Energy-Efficient Wireless LLM Inference via Uncertainty and Importance-Aware Speculative Decoding
by: Park, Jihoon, et al.
Published: (2025)

Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks
by: Lee, Kyung-hwan, et al.
Published: (2025)

Energy-Aware Dynamic Neural Inference
by: Bullo, Marcello, et al.
Published: (2024)

Energy-Aware DNN Graph Optimization
by: Wang, Yu, et al.
Published: (2020)

SparseDVFS: Sparse-Aware DVFS for Energy-Efficient Edge Inference
by: Zhang, Ziyang, et al.
Published: (2026)

HGCA: Hybrid GPU-CPU Attention for Long Context LLM Inference
by: Deng, Weishu, et al.
Published: (2025)

An Enhanced Projection Pursuit Tree Classifier with Visual Methods for Assessing Algorithmic Improvements
by: da Silva, Natalia, et al.
Published: (2026)

Interactive Graphics for Visually Diagnosing Forest Classifiers in R
by: da Silva, Natalia, et al.
Published: (2017)

Watt Counts: Energy-Aware Benchmark for Sustainable LLM Inference on Heterogeneous GPU Architectures
by: Argerich, Mauricio Fadel, et al.
Published: (2026)

Correctness-Optimized Residual Activation Lens (CORAL): Transferrable and Calibration-Aware Inference-Time Steering
by: Miao, Miranda Muqing, et al.
Published: (2026)

NanoFlux: Adversarial Dual-LLM Evaluation and Distillation For Multi-Domain Reasoning
by: Anantha, Raviteja, et al.
Published: (2025)

Learning Short-Term and Long-Term Patterns of High-Order Dynamics in Real-World Networks
by: Ko, Yunyong, et al.
Published: (2025)

Harvest: Opportunistic Peer-to-Peer GPU Caching for LLM Inference
by: Gopal, Nikhil, et al.
Published: (2026)

ModeSwitch-LLM: A Lightweight Phase-Aware Controller for Cross-Mode LLM Inference on a Single GPU
by: Sunesh, Aman, et al.
Published: (2026)

LIDS: LLM Summary Inference Under the Layered Lens
by: Park, Dylan, et al.
Published: (2026)

Transformers as Intrinsic Optimizers: Forward Inference through the Energy Principle
by: Ren, Ruifeng, et al.
Published: (2025)

Challenging GPU Dominance: When CPUs Outperform for On-Device LLM Inference
by: Zhang, Haolin, et al.
Published: (2025)

From Prompts to Power: Measuring the Energy Footprint of LLM Inference
by: Caravaca, Francisco, et al.
Published: (2025)

PULSE-ICU: A Pretrained Unified Long-Sequence Encoder for Multi-task Prediction in Intensive Care Units
by: Jang, Sejeong, et al.
Published: (2025)

Variational Inference Optimized Using the Curved Geometry of Coupled Free Energy
by: Nelson, Kenric, et al.
Published: (2025)

Scaling On-Device GPU Inference for Large Generative Models
by: Tang, Jiuqiang, et al.
Published: (2025)

New User Event Prediction Through the Lens of Causal Inference
by: Yuchi, Henry Shaowu, et al.
Published: (2024)

Efficient Edge LLMs Deployment via HessianAware Quantization and CPU GPU Collaborative
by: Zhang, Tuo, et al.
Published: (2025)

Energy Considerations of Large Language Model Inference and Efficiency Optimizations
by: Fernandez, Jared, et al.
Published: (2025)