Cover Image

HexGen-2: Disaggregated Generative Inference of LLMs in Heterogeneous Environment

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Jiang, Youhe, Yan, Ran, Yuan, Binhang
Format:	Preprint
Published:	2025
Subjects:	Distributed, Parallel, and Cluster Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

HexGen: Generative Inference of Large Language Model over Heterogeneous Environment
by: Jiang, Youhe, et al.
Published: (2023)

HexiSeq: Accommodating Long Context Training of LLMs over Heterogeneous Hardware
by: Liang, Yan, et al.
Published: (2026)

HexAGenT: Efficient Agentic LLM Serving via Workflow- and Heterogeneity-Aware Scheduling
by: Peng, You, et al.
Published: (2026)

AReaL-Hex: Accommodating Asynchronous RL Training over Heterogeneous GPUs
by: Yan, Ran, et al.
Published: (2025)

HexiScale: Facilitating Large Language Model Training over Heterogeneous Hardware
by: Yan, Ran, et al.
Published: (2024)

Parallax: Efficient LLM Inference Service over Decentralized Environment
by: Tong, Chris, et al.
Published: (2025)

Autopoiesis: A Self-Evolving System Paradigm for LLM Serving Under Runtime Dynamics
by: Jiang, Youhe, et al.
Published: (2026)

Efficient Multi-round LLM Inference over Disaggregated Serving
by: He, Wenhao, et al.
Published: (2026)

FSA: An Alternative Efficient Implementation of Native Sparse Attention Kernel
by: Yan, Ran, et al.
Published: (2025)

BOute: Cost-Efficient LLM Serving with Heterogeneous LLMs and GPUs via Multi-Objective Bayesian Optimization
by: Jiang, Youhe, et al.
Published: (2026)

Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs
by: Jiang, Youhe, et al.
Published: (2025)

Efficient Pre-Training of LLMs via Topology-Aware Communication Alignment on More Than 9600 GPUs
by: He, Guoliang, et al.
Published: (2025)

Cascadia: An Efficient Cascade Serving System for Large Language Models
by: Jiang, Youhe, et al.
Published: (2025)

StreamRL: Scalable, Heterogeneous, and Elastic RL for LLMs with Disaggregated Stream Generation
by: Zhong, Yinmin, et al.
Published: (2025)

Inference without Interference: Disaggregate LLM Inference for Mixed Downstream Workloads
by: Hu, Cunchen, et al.
Published: (2024)

Janus: Disaggregating Attention and Experts for Scalable MoE Inference
by: Zhang, Zhexiang, et al.
Published: (2025)

DistTrain: Addressing Model and Data Heterogeneity with Disaggregated Training for Multimodal Large Language Models
by: Zhang, Zili, et al.
Published: (2024)

From Attention to Disaggregation: Tracing the Evolution of LLM Inference
by: Kumar, Madabattula Rajesh, et al.
Published: (2025)

Taming the Chaos: Coordinated Autoscaling for Heterogeneous and Disaggregated LLM Inference
by: Li, Rongzhi, et al.
Published: (2025)

Proceedings of 3rd Workshop on Heterogeneous Composable and Disaggregated Systems
by: Pinto, Christian, et al.
Published: (2024)

ThunderServe: High-performance and Cost-efficient LLM Serving in Cloud Environments
by: Jiang, Youhe, et al.
Published: (2025)

DOPD: A Dynamic PD-Disaggregation Architecture for Maximizing Goodput in LLM Inference Serving
by: Liao, Junhan, et al.
Published: (2025)

Arrow: Adaptive Scheduling Mechanisms for Disaggregated LLM Inference Architecture
by: Wu, Yu, et al.
Published: (2025)

CaraServe: CPU-Assisted and Rank-Aware LoRA Serving for Generative LLM Inference
by: Li, Suyi, et al.
Published: (2024)

Lotus: Optimizing Disaggregated Transactions with Disaggregated Locks
by: Hu, Zhisheng, et al.
Published: (2025)

Taming Request Imbalance: SLO-Aware Scheduling for Disaggregated LLM Inference
by: Wang, Qipeng
Published: (2026)

Cronus: Efficient LLM inference on Heterogeneous GPU Clusters via Partially Disaggregated Prefill
by: Liu, Yunzhao, et al.
Published: (2025)

HetRL: Efficient Reinforcement Learning for LLMs in Heterogeneous Environments
by: He, Yongjun, et al.
Published: (2025)

OServe: Accelerating LLM Serving via Spatial-Temporal Workload Orchestration
by: Jiang, Youhe, et al.
Published: (2026)

TD-Pipe: Temporally-Disaggregated Pipeline Parallelism Architecture for High-Throughput LLM Inference
by: Zhang, Hongbin, et al.
Published: (2025)

KVDirect: Distributed Disaggregated LLM Inference
by: Chen, Shiyang, et al.
Published: (2024)

Disaggregated Prefill and Decoding Inference System for Large Language Model Serving on Multi-Vendor GPUs
by: Chen, Xing, 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)

HACK: Homomorphic Acceleration via Compression of the Key-Value Cache for Disaggregated LLM Inference
by: Zhang, Zeyu, et al.
Published: (2025)

HeteGen: Heterogeneous Parallel Inference for Large Language Models on Resource-Constrained Devices
by: Zhao, Xuanlei, et al.
Published: (2024)

Revisiting the Time Cost Model of AllReduce
by: Xiong, Dian, et al.
Published: (2024)

Efficient Heterogeneous Large Language Model Decoding with Model-Attention Disaggregation
by: Chen, Shaoyuan, et al.
Published: (2024)

LMDeploy Accelerates Mixed-Precision LLM Inference with TurboMind
by: Zhang, Li, et al.
Published: (2025)

Software Resource Disaggregation for HPC with Serverless Computing
by: Copik, Marcin, et al.
Published: (2024)

Beyond the Buzz: A Pragmatic Take on Inference Disaggregation
by: Mitra, Tiyasa, et al.
Published: (2025)