Ring-Attention
A distributed attention implementation that partitions long sequences into blocks across multiple GPUs. KV blocks are passed sequentially along a ring topology and partial attention results are accumulated, decoupling per-GPU memory usage from sequence length.
Timeline (last 90 days)
Ring-Attention splits the sequence across multiple GPUs and gradually aggregates attention results through ring communication; each round of computation must wait for the previous round's KV block to arrive, forming a serial dependency chain.
The paper evaluates multiple hardware architectures on both forward and backward algorithms, all outperforming the current state-of-the-art method (Ring-Attention).
On a dual-NUMA PCIe architecture, CHARM+ achieves an average forward speedup of 1.3x and an average backward speedup of 1.7x, compared against Ring-Attention.
All Facts (3)
Ring-Attention splits the sequence across multiple GPUs and gradually aggregates attention results through ring communication; each round of computation must wait for the previous round's KV block to arrive, forming a serial dependency chain.
50%UnverifiedThe paper evaluates multiple hardware architectures on both forward and backward algorithms, all outperforming the current state-of-the-art method (Ring-Attention).
50%UnverifiedOn a dual-NUMA PCIe architecture, CHARM+ achieves an average forward speedup of 1.3x and an average backward speedup of 1.7x, compared against Ring-Attention.
50%