Copertina

DeInfer: Efficient Parallel Inferencing for Decomposed Large Language Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Huang, You-Liang, Huang, Xinhao, Liao, Chengxi, Wen, Zeyi
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Computation and Language Distributed, Parallel, and Cluster Computing
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

InferCept: Efficient Intercept Support for Augmented Large Language Model Inference
di: Abhyankar, Reyna, et al.
Pubblicazione: (2024)

SpecInfer: Accelerating Generative Large Language Model Serving with Tree-based Speculative Inference and Verification
di: Miao, Xupeng, et al.
Pubblicazione: (2023)

Quasar: Quantized Self-Speculative Acceleration for Rapid Inference via Memory-Efficient Verification
di: Huang, Guang, et al.
Pubblicazione: (2026)

Folding Tensor and Sequence Parallelism for Memory-Efficient Transformer Training & Inference
di: Shyam, Vasu, et al.
Pubblicazione: (2026)

Inference Acceleration for Large Language Models on CPUs
di: PS, Ditto, et al.
Pubblicazione: (2024)

BlockBPE: Parallel BPE Tokenization
di: You, Amos
Pubblicazione: (2025)

LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models
di: Park, Gunho, et al.
Pubblicazione: (2022)

InternEvo: Efficient Long-sequence Large Language Model Training via Hybrid Parallelism and Redundant Sharding
di: Chen, Qiaoling, et al.
Pubblicazione: (2024)

SLO-Aware Scheduling for Large Language Model Inferences
di: Huang, Jinqi, et al.
Pubblicazione: (2025)

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

A Federated and Parameter-Efficient Framework for Large Language Model Training in Medicine
di: Li, Anran, et al.
Pubblicazione: (2026)

Minions: Accelerating Large Language Model Inference with Aggregated Speculative Execution
di: Wang, Siqi, et al.
Pubblicazione: (2024)

Decouple and Decompose: Scaling Resource Allocation with DeDe
di: Xu, Zhiying, et al.
Pubblicazione: (2024)

HydraInfer: Hybrid Disaggregated Scheduling for Multimodal Large Language Model Serving
di: Dong, Xianzhe, et al.
Pubblicazione: (2025)

PipeInfer: Accelerating LLM Inference using Asynchronous Pipelined Speculation
di: Butler, Branden, et al.
Pubblicazione: (2024)

Enhancing Memory Efficiency in Large Language Model Training Through Chronos-aware Pipeline Parallelism
di: Lin, Xinyuan, et al.
Pubblicazione: (2025)

Energy-Efficient Split Learning for Fine-Tuning Large Language Models in Edge Networks
di: Li, Zuguang, et al.
Pubblicazione: (2024)

CkIO: Parallel File Input for Over-Decomposed Task-Based Systems
di: Jacob, Mathew, et al.
Pubblicazione: (2024)

HAP: Hybrid Adaptive Parallelism for Efficient Mixture-of-Experts Inference
di: Lin, Haoran, et al.
Pubblicazione: (2025)

EPS-MoE: Expert Pipeline Scheduler for Cost-Efficient MoE Inference
di: Qian, Yulei, et al.
Pubblicazione: (2024)

Conveyor: Efficient Tool-aware LLM Serving with Tool Partial Execution
di: Xu, Yechen, et al.
Pubblicazione: (2024)

Seq1F1B: Efficient Sequence-Level Pipeline Parallelism for Large Language Model Training
di: Sun, Ao, et al.
Pubblicazione: (2024)

SiDP: Memory-Efficient Data Parallelism for Offline LLM Inference
di: Zhao, Alan, et al.
Pubblicazione: (2026)

An Efficient Heterogeneous Co-Design for Fine-Tuning on a Single GPU
di: Yang, Ruijia, et al.
Pubblicazione: (2026)

Ghidorah: Fast LLM Inference on Edge with Speculative Decoding and Hetero-Core Parallelism
di: Wei, Jinhui, et al.
Pubblicazione: (2025)

SPECTRE: Hybrid Ordinary-Parallel Speculative Serving for Resource-Efficient LLM Inference
di: Xie, Jincheng, et al.
Pubblicazione: (2026)

FLYING SERVING: On-the-Fly Parallelism Switching for Large Language Model Serving
di: Gao, Shouwei, et al.
Pubblicazione: (2026)

Collaborative Inference for Large Models with Task Offloading and Early Exiting
di: Xie, Zuan, et al.
Pubblicazione: (2024)

CFP: Efficient Optimization of Intra-Operator Parallelism Plans for Large Model Training
di: Hu, Weifang, et al.
Pubblicazione: (2025)

Hybrid-Parallel: Achieving High Performance and Energy Efficient Distributed Inference on Robots
di: Sun, Zekai, et al.
Pubblicazione: (2024)

FlexLLM: Token-Level Co-Serving of LLM Inference and Finetuning with SLO Guarantees
di: Oliaro, Gabriele, et al.
Pubblicazione: (2024)

Split Fine-Tuning for Large Language Models in Wireless Networks
di: Zhang, Songge, et al.
Pubblicazione: (2025)

LLMTailor: A Layer-wise Tailoring Tool for Efficient Checkpointing of Large Language Models
di: Sun, Minqiu, et al.
Pubblicazione: (2026)

AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs
di: Lin, Wenxiang, et al.
Pubblicazione: (2026)

Extending Contract Verification for Parallel Programming Models to Fortran
di: Oraji, Yussur Mustafa, et al.
Pubblicazione: (2026)

Communication-Efficient Collaborative LLM Inference over LEO Satellite Networks
di: Zhang, Songge, et al.
Pubblicazione: (2026)

EPIC: Efficient Position-Independent Caching for Serving Large Language Models
di: Hu, Junhao, et al.
Pubblicazione: (2024)

Verifying Properties of Index Arrays in a Purely-Functional Data-Parallel Language
di: Hinnerskov, Nikolaj Hey, et al.
Pubblicazione: (2025)

Distributed Speculative Inference (DSI): Speculation Parallelism for Provably Faster Lossless Language Model Inference
di: Timor, Nadav, et al.
Pubblicazione: (2024)

Efficient Parallel Compilation and Profiling of Quantum Circuits at Large Scales
di: Moore, Jane, et al.
Pubblicazione: (2026)