Paper page - Optimized Network Architectures for Large Language Model Training with Billions of Parameters
Abstract This paper challenges the well-established paradigm for building any-to-any networks for training Large Language Models (LLMs). We show that LLMs exhibit a unique communication pattern where only small groups of GPUs require high-bandwidth any-to-any communication within them, to achieve near-optimal training performance. Across these groups of GPUs, the communication is insignificant, sp
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How to Build Low-cost Networks for Large Language Models (without Sacrificing Performance)?
https://arxiv.org/pdf/2307.12169.pdf
