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1、Advanced Networks for Artifcial Intelligence and Machine Learning ComputingScaling Fiber Networks to Meet Tomorrows Data Center Demands2Copyright 2024 AFL.All rights reserved.Executive SummaryThis document explores the critical considerations linked to data centers optimized for AI workloads.By high

2、lighting the growing computational power required by large language models(LLMs),the paper seeks to inform readers on the necessity for advanced networking and innovative physical layer solutions.This overview of AI data center infrastructure,hardware requirements,and capabilities provides the groun

3、dwork for a forthcoming comprehensive exploration of in-depth technical considerations.Due to the energy required by high-performance hardware and the complexity and size of the datasets needed for LLM training and inference,AI data centers present signifcantly higher power demands compared to tradi

4、tional hyperscale architectures.To accommodate very large systems with specialized hardware and cooling systems,AI data center size both in terms of physical footprint and cubic meters has grown and continues to grow,with future projects indicating even greater space requirements.From sharing model

5、updates during training to low-latency connections between accelerators,discover the essential load balancing and network control mechanisms behind the dynamic demands of AI workloads.AI workloads generate signifcant heat,necessitating advanced thermal management methods such as direct-to-chip and i

6、mmersion cooling traditional air-cooling methods cannot meet the cooling requirements of high-density AI data center environments.Choice of network topology defnes a systems data fow effciency and readiness for rapid scalability.With the aim of minimizing latency and maximizing bandwidth,operators m