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But not, while the succession duration develops, the general efficiency reduces. The brand new linear layers from the prefill stage are mostly calculate-bound (discover ‘qkv mlp init‘ and ‘up/gate/off init‘). In the decoding phase, the newest datapoints of your linear coating setting a column for the exact same slope since the GPU’s memories bandwidth (see ‘qkv mlp ar‘ and ‘up/gate/down ar‘). It appears the fresh linear layers on the decoding stage are also bounded because of the memories data transfer. Increasing the group dimensions improves the reached FLOP/s and Working Intensity below recollections data transfer limitations thanks to finest parallelism.
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I expose a diagnosis of your own roofline model for different workers within the large vocabulary models (LLMs), especially targeting Llama-7B, Llama-13B, and you will Llama-33B (Touvron et al., 2023). These types of habits were benchmarked to the additional GPUs, such as the A100-80GB-PCIe, A40, and you will A6000. We investigated the three categories of matrix multiplication providers while the it portray the main sourced elements of computational overhead during these models. Our analysis follows the brand new report (Chen, 2023) and that discusses the effectiveness of group proportions but ours focuses far more on the decryption and you can synchronous decoding. The way in which in which text message is tested from Higher Language Models (LLMs) is also significantly determine the standard of the brand new generated output.
