Výsledky vyhledávání - Distributed and parallelized LLM training

A multilevel algorithm for scalable independent task assignment.

Autoři: Burhan Tabak, H. Kartal Tabak, E. Aykanat, Cevdet

Zdroj: Future Generation Computer Systems. Mar2026, Vol. 176, pN.PAG-N.PAG. 1p.

Témata: *ALGORITHMS, *PARALLEL programming, *HEURISTIC, HETEROGENEOUS computing, CLOUD computing, TIME complexity, DESIGN

LLM Inference Acceleration via Efficient Operation Fusion

Autoři: Salmani, Mahsa Soloveychik, Ilya

Témata: Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Hardware Architecture, text

URL: http://arxiv.org/abs/2502.17728

MobiZO: Enabling Efficient LLM Fine-Tuning at the Edge via Inference Engines

Autoři: Gao, Lei Ziashahabi, Amir Niu, Yue a další

Témata: Machine Learning, FOS: Computer and information sciences, Distributed, Parallel, and Cluster Computing, Distributed, Parallel, and Cluster Computing (cs.DC), Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2409.15520

FLAD: Federated Learning for LLM-based Autonomous Driving in Vehicle-Edge-Cloud Networks

Autoři: Xiang, Tianao Zhi, Mingjian Bi, Yuanguo a další

Témata: Machine Learning

Relation: http://arxiv.org/abs/2511.09025

Dostupnost: http://arxiv.org/abs/2511.09025

Enabling Efficient On-Device Fine-Tuning of LLMs Using Only Inference Engines

Autoři: Gao, Lei Ziashahabi, Amir Niu, Yue a další

Témata: Computer Science - Machine Learning, Computer Science - Distributed, Parallel, and Cluster Computing, text

URL: http://arxiv.org/abs/2409.15520

SWattention: designing fast and memory-efficient attention for a new Sunway Supercomputer.

Autoři: Wu, Ruohan Zhu, Xianyu Chen, Junshi a další

Zdroj: Journal of Supercomputing; Jul2024, Vol. 80 Issue 10, p13657-13680, 24p

Témata: LANGUAGE models, SUPERCOMPUTERS, ARTIFICIAL intelligence

AI Computing Systems for Large Language Models Training.

Autoři: Zhang, Zhen-Xing Wen, Yuan-Bo Lyu, Han-Qi a další

Zdroj: Journal of Computer Science & Technology (10009000); Jan2025, Vol. 40 Issue 1, p6-41, 36p

Témata: LANGUAGE models, COMPUTATIONAL mathematics, ARTIFICIAL intelligence, DISTRIBUTED computing, HETEROGENEOUS distributed computing, BOOSTING algorithms

AI at Scale: The Infrastructure Revolution Enabling GPT-Class Large Language Models.

Autoři: Nandamuri, Sravankumar

Zdroj: Journal of Computer Science & Technology Studies; 2025, Vol. 7 Issue 4, p321-328, 8p

Témata: LANGUAGE models, DISRUPTIVE innovations, ARTIFICIAL intelligence, GENERATIVE pre-trained transformers, SYSTEMS software

LLMs for Cybersecurity in the Big Data Era: A Comprehensive Review of Applications, Challenges, and Future Directions.

Autoři: Karras, Aristeidis Theodorakopoulos, Leonidas Karras, Christos a další

Zdroj: Information; Nov2025, Vol. 16 Issue 11, p957, 72p

Témata: BIG data, LANGUAGE models, INTERNET security, ANOMALY detection (Computer security), RISK assessment

Large-Language-Model-Enabled Text Semantic Communication Systems.

Autoři: Wang, Zhenyi Zou, Li Wei, Shengyun a další

Zdroj: Applied Sciences (2076-3417); Jul2025, Vol. 15 Issue 13, p7227, 23p

Témata: LANGUAGE models, NATURAL language processing, DIGITAL communications, SIGNAL-to-noise ratio, TELECOMMUNICATION systems, DECODING algorithms

What is next for LLMs? Pushing the boundaries of next-gen AI computing hardware with photonic chips.

Autoři: Li, Renjie Xin, Qi Wei, Wenjie a další

Zdroj: Nanophotonics (21928606); Nov2025, Vol. 14 Issue 22, p3499-3525, 27p

Témata: ENERGY consumption, INTEGRATED optics, MATRIX multiplications, SYSTEM integration, ARTIFICIAL neural networks, TRANSFORMER models, TWO-dimensional materials (Nanotechnology)

A computationally efficient parallel training framework for solving integral equations using deep learning methods.

Autoři: Ren, Zhiyuan Liu, Dong Liao, Zhen a další

Zdroj: AIMS Mathematics; 2025, Vol. 10 Issue 10, p1-38, 38p

Témata: INTEGRAL equations, DEEP learning, MECHANICAL efficiency, PARALLEL programming, SCIENTIFIC computing, PARALLEL processing

Efficient Federated Learning with Heterogeneous Data and Adaptive Dropout.

Autoři: Liu, Ji Ma, Beichen Yu, Qiaolin a další

Zdroj: ACM Transactions on Knowledge Discovery from Data; Sep2025, Vol. 19 Issue 8, p1-31, 31p

Témata: FEDERATED learning, DATA distribution, ENSEMBLE learning, DISTRIBUTED databases, MATHEMATICAL optimization

Efficient Compressing and Tuning Methods for Large Language Models: A Systematic Literature Review.

Autoři: Kim, Gun Il Hwang, Sunga Jang, Beakcheol

Zdroj: ACM Computing Surveys; Oct2025, Vol. 57 Issue 10, p1-39, 39p

Témata: LANGUAGE models, ARTIFICIAL neural networks, MACHINE learning, GENERATIVE pre-trained transformers, NATURAL language processing, MACHINE translating, STATIC random access memory

The Rise of Reinforcement Learning in AI: From Theory to Distributed Systems Implementation.

Autoři: Sundi, Jyotirmoy

Zdroj: Journal of Computer Science & Technology Studies; 2025, Vol. 7 Issue 8, p385-392, 8p

Témata: COMPUTATIONAL intelligence, SUPERVISED learning, ARTIFICIAL intelligence, LEARNING, SYSTEMS theory

Privacy-Preserving Clinical Decision Support for Emergency Triage Using LLMs: System Architecture and Real-World Evaluation.

Autoři: Karamanlıoğlu, Alper Demirel, Berkan Tural, Onur a další

Zdroj: Applied Sciences (2076-3417); Aug2025, Vol. 15 Issue 15, p8412, 31p

Témata: CLINICAL decision support systems, LANGUAGE models, DATA privacy, DATA protection, ON-site evaluation, FEDERATED learning, MEDICAL technology

A Survey: Collaborative Hardware and Software Design in the Era of Large Language Models.

Autoři: Guo, Cong Cheng, Feng Du, Zhixu a další

Zdroj: IEEE Circuits & Systems Magazine; 2025 Q1, Vol. 25 Issue 1, p35-57, 23p

A Review on Edge Large Language Models: Design, Execution, and Applications.

Autoři: Zheng, Yue Chen, Yuhao Qian, Bin a další

Zdroj: ACM Computing Surveys; Aug2025, Vol. 57 Issue 8, p1-35, 35p

Témata: LANGUAGE models, DESIGN, SUBROUTINES (Computer programs)

Research on the Training and Application Methods of a Lightweight Agricultural Domain-Specific Large Language Model Supporting Mandarin Chinese and Uyghur.

Autoři: Pan, Kun Zhang, Xiaogang Chen, Liping

Zdroj: Applied Sciences (2076-3417); Jul2024, Vol. 14 Issue 13, p5764, 31p

Témata: LANGUAGE models, UIGHUR (Turkic people), NATURAL language processing, MANDARIN dialects, AGRICULTURE, AGRICULTURAL technology, MACHINE translating

A Second-Classroom Personalized Learning Path Recommendation System Based on Large Language Model Technology.

Autoři: Yang, Qiankun Liang, Changyong

Zdroj: Applied Sciences (2076-3417); Jul2025, Vol. 15 Issue 14, p7655, 22p

Témata: RECOMMENDER systems, LANGUAGE models, STUDENT development, INDIVIDUALIZED instruction, DATA integration, GENERATIVE adversarial networks, GENERATIVE pre-trained transformers, MACHINE learning