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Songlin Yang

Personal blog · sustcsonglin.github.io/blogaiprogramming

Songlin Yang writes blank, a personal blog at sustcsonglin.github.io about ai and programming. Since 2024, 4 different Hacker News readers have linked it 6 times, most often “DeltaNet Explained (Part 1)”. It is still writing: the last post was on 2024-12-03, and you can follow it by feed.

Visit the blog
6mentions?
4HN people?
2024–2026first – last linked?
Links on Hacker News per year · peak 4 in 2025

Too few sampled comments (2) to say how often HN recommends it.?

Why HN links it

HN readers link this DeltaNet-2 post to explain the chunkwise parallel algorithm, which combines parallel subsequence computation with recurrent updates between chunks for fast RNN kernels.

Summarised by Claude from a sample of 2 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.

A simple, whitespace theme for academics. Based on [*folio](https://github.com/bogoli/-folio) design.

Most-linked posts?

  1. DeltaNet Explained (Part 1)
    3 people · 4 mentions · first linked 2024-12-13

What Hacker News says?

  1. tripplyons · 2025-09-22Recommends
    Have you explored chunkwise parallel approaches? They use the O(n log n) parallel algorithm within a subsequence and update bewteen chunks recurrently like the O(n) recurrent algorithm. These are usually the fastest kernels for these kinds of RNNs. Here is the best explanation I have seen: https://sustcsonglin.github.io/blog/2024/deltanet-2/

    Comment linking /blog/2024/deltanet-2/

    on “Were RNNs all we needed? A GPU programming perspective”
  2. Submitted DeltaNet Explained (Part 1) as a story · 2 points

    HN discussion
  3. tripplyons · 2025-09-22Recommends
    Typically the fastest approaches for associative RNNs combine the advantages of the parallel O(n log n) algorithm with a recurrent non-parallel O(n) approach by computing results for subsequence chunks in parallel and moving to the next chunk in a recurrent manner. This blog post explains the method (chunkwise parallel algorithm) well: https://sustcsonglin.github.io/blog/2024/deltanet-2/

    Comment linking /blog/2024/deltanet-2/

    on “Were RNNs all we needed? A GPU programming perspective”
  4. Submitted DeltaNet Explained as a story · 2 points

    HN discussion
  5. Submitted DeltaNet Explained as a story · 1 points

    HN discussion
  6. Submitted DeltaNet Explained (Part I) as a story · 1 points

    HN discussion

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