Linear Attention Sequence Parallel (LASP): An Efficient Machine Learning Method Tailored to Linear Attention-Based Language Models

Linear attention-based models are gaining attention for their faster processing speed and comparable performance to Softmax transformers. However, large language models (LLMs), due to their large size and longer sequence lengths, exert significant strain on contemporary GPU hardware because a single GPU’s memory confines a language model’s maximum sequence length. Sequence Parallelism (SP) techniques are […]

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