The 1/W Law: An Analytical Study of Context-Length Routing Topology and GPU Generation Gains for LLM Inference Energy Efficiency
Fuente:
arXiv
Saved in:
| Main Authors: | Chen, Huamin, Liu, Xunzhuo, Liu, Yuhan, Jiang, Junchen, He, Bowei, Liu, Xue |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
FleetOpt: Analytical Fleet Provisioning for LLM Inference with Compress-and-Route as Implementation Mechanism
by: Chen, Huamin, et al.
Published: (2026)
by: Chen, Huamin, et al.
Published: (2026)
Token-Budget-Aware Pool Routing for Cost-Efficient LLM Inference
by: Chen, Huamin, et al.
Published: (2026)
by: Chen, Huamin, et al.
Published: (2026)
inference-fleet-sim: A Queueing-Theory-Grounded Fleet Capacity Planner for LLM Inference
by: Chen, Huamin, et al.
Published: (2026)
by: Chen, Huamin, et al.
Published: (2026)
The Workload-Router-Pool Architecture for LLM Inference Optimization: A Vision Paper from the vLLM Semantic Router Project
by: Chen, Huamin, et al.
Published: (2026)
by: Chen, Huamin, et al.
Published: (2026)
DAK: Direct-Access-Enabled GPU Memory Offloading with Optimal Efficiency for LLM Inference
by: Lin, Shouxu, et al.
Published: (2026)
by: Lin, Shouxu, et al.
Published: (2026)
PipeMax: Enhancing Offline LLM Inference on Commodity GPU Servers
by: Zhang, Hongbin, et al.
Published: (2026)
by: Zhang, Hongbin, et al.
Published: (2026)
Scaling Up Throughput-oriented LLM Inference Applications on Heterogeneous Opportunistic GPU Clusters with Pervasive Context Management
by: Phung, Thanh Son, et al.
Published: (2025)
by: Phung, Thanh Son, et al.
Published: (2025)
SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference
by: He, Yongchao, et al.
Published: (2025)
by: He, Yongchao, et al.
Published: (2025)
Zorse: Optimizing LLM Training Efficiency on Heterogeneous GPU Clusters
by: Guo, Runsheng Benson, et al.
Published: (2025)
by: Guo, Runsheng Benson, et al.
Published: (2025)
Efficiently Executing High-throughput Lightweight LLM Inference Applications on Heterogeneous Opportunistic GPU Clusters with Pervasive Context Management
by: Phung, Thanh Son, et al.
Published: (2025)
by: Phung, Thanh Son, et al.
Published: (2025)
SIMPLE: Disaggregating Sampling from GPU Inference into a Decision Plane for Faster Distributed LLM Serving
by: Zhao, Bohan, et al.
Published: (2025)
by: Zhao, Bohan, et al.
Published: (2025)
GCAPS: GPU Context-Aware Preemptive Priority-based Scheduling for Real-Time Tasks
by: Wang, Yidi, et al.
Published: (2024)
by: Wang, Yidi, et al.
Published: (2024)
Exploring the Efficiency of 3D-Stacked AI Chip Architecture for LLM Inference with Voxel
by: Liu, Yiqi, et al.
Published: (2026)
by: Liu, Yiqi, et al.
Published: (2026)
KV Cache Compression for Inference Efficiency in LLMs: A Review
by: Liu, Yanyu, et al.
Published: (2025)
by: Liu, Yanyu, et al.
Published: (2025)
Cronus: Efficient LLM inference on Heterogeneous GPU Clusters via Partially Disaggregated Prefill
by: Liu, Yunzhao, et al.
Published: (2025)
by: Liu, Yunzhao, et al.
Published: (2025)
APEX: Asynchronous Parallel CPU-GPU Execution for Online LLM Inference on Constrained GPUs
by: Fan, Jiakun, et al.
Published: (2025)
by: Fan, Jiakun, et al.
Published: (2025)
CLLoRA: An Approach to Measure the Effects of the Context Length for LLM Fine-Tuning
by: Zhang, Ping, et al.
Published: (2025)
by: Zhang, Ping, et al.
Published: (2025)
Efficient Routing of Inference Requests across LLM Instances in Cloud-Edge Computing
by: Yu, Shibo, et al.
Published: (2025)
by: Yu, Shibo, et al.
Published: (2025)
Accuracy Is Speed: Towards Long-Context-Aware Routing for Distributed LLM Serving
by: Yoshimura, Takeshi, et al.
Published: (2026)
by: Yoshimura, Takeshi, et al.
Published: (2026)
A Preliminary Study on Accelerating Simulation Optimization with GPU Implementation
by: He, Jinghai, et al.
Published: (2024)
by: He, Jinghai, et al.
Published: (2024)
Watt Counts: Energy-Aware Benchmark for Sustainable LLM Inference on Heterogeneous GPU Architectures
by: Argerich, Mauricio Fadel, et al.
Published: (2026)
by: Argerich, Mauricio Fadel, et al.
Published: (2026)
HybridFlow: Resource-Adaptive Subtask Routing for Efficient Edge-Cloud LLM Inference
by: Dong, Jiangwen, et al.
Published: (2025)
by: Dong, Jiangwen, et al.
Published: (2025)
LLM Inference at the Edge: Mobile, NPU, and GPU Performance Efficiency Trade-offs Under Sustained Load
by: Tummalapalli, Pranay, et al.
Published: (2026)
by: Tummalapalli, Pranay, et al.
Published: (2026)
CALVO: Improve Serving Efficiency for LLM Inferences with Intense Network Demands
by: Wang, Weiye, et al.
Published: (2026)
by: Wang, Weiye, et al.
Published: (2026)
Combining GPU and CPU for accelerating evolutionary computing workloads
by: Eynaliyev, Rustam, et al.
Published: (2025)
by: Eynaliyev, Rustam, et al.
Published: (2025)
Optimal Resource Efficiency with Fairness in Heterogeneous GPU Clusters
by: Mo, Zizhao, et al.
Published: (2024)
by: Mo, Zizhao, et al.
Published: (2024)
KIS-S: A GPU-Aware Kubernetes Inference Simulator with RL-Based Auto-Scaling
by: Zhang, Guilin, et al.
Published: (2025)
by: Zhang, Guilin, et al.
Published: (2025)
70% Size, 100% Accuracy: Lossless LLM Compression for Efficient GPU Inference via Dynamic-Length Float (DFloat11)
by: Zhang, Tianyi, et al.
Published: (2025)
by: Zhang, Tianyi, et al.
Published: (2025)
Offline Energy-Optimal LLM Serving: Workload-Based Energy Models for LLM Inference on Heterogeneous Systems
by: Wilkins, Grant, et al.
Published: (2024)
by: Wilkins, Grant, et al.
Published: (2024)
ParvaGPU: Efficient Spatial GPU Sharing for Large-Scale DNN Inference in Cloud Environments
by: Lee, Munkyu, et al.
Published: (2024)
by: Lee, Munkyu, et al.
Published: (2024)
PrefillOnly: An Inference Engine for Prefill-only Workloads in Large Language Model Applications
by: Du, Kuntai, et al.
Published: (2025)
by: Du, Kuntai, et al.
Published: (2025)
Predictable LLM Serving on GPU Clusters
by: Darzi, Erfan, et al.
Published: (2025)
by: Darzi, Erfan, et al.
Published: (2025)
Heat: Satellite's meat is GPU's poison
by: Yuan, Zhehu, et al.
Published: (2024)
by: Yuan, Zhehu, et al.
Published: (2024)
Characterization-Guided GPU Fault Resilience in NVIDIA MPS
by: Liu, Rixin, et al.
Published: (2026)
by: Liu, Rixin, et al.
Published: (2026)
Decentralized LLM Inference over Edge Networks with Energy Harvesting
by: Khoshsirat, Aria, et al.
Published: (2024)
by: Khoshsirat, Aria, et al.
Published: (2024)
Efficient Multi-round LLM Inference over Disaggregated Serving
by: He, Wenhao, et al.
Published: (2026)
by: He, Wenhao, et al.
Published: (2026)
Fantasy: Efficient Large-scale Vector Search on GPU Clusters with GPUDirect Async
by: Liu, Yi, et al.
Published: (2025)
by: Liu, Yi, et al.
Published: (2025)
Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs
by: Jiang, Youhe, et al.
Published: (2025)
by: Jiang, Youhe, et al.
Published: (2025)
HAS-GPU: Efficient Hybrid Auto-scaling with Fine-grained GPU Allocation for SLO-aware Serverless Inferences
by: Gu, Jianfeng, et al.
Published: (2025)
by: Gu, Jianfeng, et al.
Published: (2025)
Revisiting Federated Fine-Tuning: A Single Communication Round is Enough for Foundation Models
by: Wang, Ziyao, et al.
Published: (2024)
by: Wang, Ziyao, et al.
Published: (2024)
Similar Items
-
FleetOpt: Analytical Fleet Provisioning for LLM Inference with Compress-and-Route as Implementation Mechanism
by: Chen, Huamin, et al.
Published: (2026) -
Token-Budget-Aware Pool Routing for Cost-Efficient LLM Inference
by: Chen, Huamin, et al.
Published: (2026) -
inference-fleet-sim: A Queueing-Theory-Grounded Fleet Capacity Planner for LLM Inference
by: Chen, Huamin, et al.
Published: (2026) -
The Workload-Router-Pool Architecture for LLM Inference Optimization: A Vision Paper from the vLLM Semantic Router Project
by: Chen, Huamin, et al.
Published: (2026) -
DAK: Direct-Access-Enabled GPU Memory Offloading with Optimal Efficiency for LLM Inference
by: Lin, Shouxu, et al.
Published: (2026)