构建和训练超大模型是当前人工智能领域最具挑战性的任务之一,其成功依赖于多维度技术要素与资源的协同整合。从硬件基础设施到算法创新,从数据管理到能源优化,每个环节均需突破传统深度学习框架的局限性。本文将系统性地探讨支撑超大模型训练的核心技术体系与资源要求,揭示其复杂性与内在关联性。在硬件层面,算力集群的构建是基础前提。当前主流的解决方案依赖于大规模GPU或TPU集群,其中NVIDIA H100、...
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