https://hackerpaper.kaipfister.de/p/2506.04667/Collected HN comments and submissions linking this paper.enMon, 02 Nov 2026 11:16:22 GMThttps://news.ycombinator.com/item?id=44322313urn:hackerpapers:mention:2506.04667:44322313Thu, 19 Jun 2025 20:36:31 GMT<p>This is very cool. I enjoyed going through the writeup and GitHub README. I was wondering if these same optimizations can be brought to bear on training as well, rather than only inference. I guess the challenge here is fusing backward computations with gradient communication. I also saw that this currently does not handle dynamic workloads such as MoE. I recently came across this paper that does exactly this: FlashDMoE: Fast Distributed MoE in a Single Kernel - https://arxiv.org/pdf/2506.04667</p><p><a href="https://hackerpaper.kaipfister.de/p/2506.04667/">Paper and discussion history</a>. A mention is not an endorsement.</p>cs.DC