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Lightweight CPU Replication Explores Kimi K3 KDA Parallelism

AI summary

The second part of the author's lightweight, CPU-only replication of Kimi Delta Attention in Kimi K3 examines ShortConv, recurrent state updates, chunkwise parallelism, context parallelism and decoding caches. The author reports a KCP prefix-scan error of 1.110e-16 and 37 passing tests in their own test suite. The report also notes that larger chunks can increase memory use, while floating-point errors and numerical-stability limits constrain chunk and tile sizes.

In-depth insight

The report provides implementation details, numerical experiments and test results illustrating the tradeoffs between within-chunk parallelism, recurrent state dependencies across chunks, and numerical stability.

Some source content is omitted. Continue reading on the original site.

#Kimi K3#Kimi Delta Attention#KDACache#KDA Context Parallelism#DPLR

Original · 33 min readRead the original
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