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A Review on Proprietary Accelerators for Large Language Models

Performance 2025-03-14 v1 Hardware Architecture

Abstract

With the advancement of Large Language Models (LLMs), the importance of accelerators that efficiently process LLM computations has been increasing. This paper discusses the necessity of LLM accelerators and provides a comprehensive analysis of the hardware and software characteristics of the main commercial LLM accelerators. Based on this analysis, we propose considerations for the development of next-generation LLM accelerators and suggest future research directions.

Keywords

Cite

@article{arxiv.2503.09650,
  title  = {A Review on Proprietary Accelerators for Large Language Models},
  author = {Sihyeong Park and Jemin Lee and Byung-Soo Kim and Seokhun Jeon},
  journal= {arXiv preprint arXiv:2503.09650},
  year   = {2025}
}

Comments

4 pages, accepted in AICompS 2024

R2 v1 2026-06-28T22:17:58.826Z