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Zyphra, an AI lab, has developed a new algorithm called Tree Attention, which is designed for topology-aware decoding in long-context attention on GPU clusters. This approach is noted for its efficiency, requiring less communication and memory than the existing Ring Attention method. Tree Attention enables more efficient scaling to million token sequence lengths and allows for cross-device decoding to be performed asymptotically faster, up to eight times faster than alternative approaches. This development is particularly significant for parallelizing attention computation across multiple GPUs, making it a noteworthy advancement in the field of AI.
Tree Attention: Topology-aware Decoding for Long-Context Attention on GPU clusters https://t.co/HI9EY9y6fQ https://t.co/KWCS6RQsGF
Looks like a great paper, for parallelizing attention computation across multiple GPUs. 👏 Tree attention algo, enables cross-device decoding to be performed asymptotically faster (up to 8x faster) than alternative approaches such as Ring Attention, while also requiring… https://t.co/dIw0Sizoxk
Zyphra is one of the most underrated AI labs right now Great work on Tree Attention, an exact attention approach with less communication and memory requirements than Ring Attention, enabling more efficient scaling to million token sequence lengths https://t.co/V1lSFUSzLF https://t.co/CVAkCfGapi
