Skip to content
HomeVideos
AllLongsCategoriesPlaylists
BooksBlogsPodcasts
HistoryListsWatch laterLiked videosFollowing

The videos, books, blogs and podcasts Hacker News keeps recommending, all in one place.

VideosBooksBlogsPodcastsAboutPrivacySettings

Data from Hacker News, HackerTube, HackerBooks, HackerBlogs and Open Library. Credits · Not affiliated with Y Combinator.

HomeVideosBooksBlogsPodcasts
Ctrl K

    High-performance Tree Wrangling, the APL Way // Aaron Hsu // Dyalog '18

    Dyalog User Meetings

    3 HN recommenders · recommended in 3 months, 2019–2021

    YouTube

    30:37 · 5.8K views · Nov 30, 2018

    Aaron Hsu shows how to manipulate and transform tree data in APL using arrays and inverted tables instead of pointers. He claims much smaller code, better performance and easier parallelisation.

    HN recommends it as a striking example of high-performance tree handling with array programming.

    Software Engineering & LanguagesProgramming language designAlgorithms & data structuresSoftware performance & optimization
    1. 54:31
      Does APL Need a Type System? by Aaron W Hsu at #FnConf18ConfEngine6.4K views • 7 years ago
    2. 54:10
      Design Patterns vs Anti pattern in APL by Aaron W Hsu at FnConf17ConfEngine7.7K views • 8 years ago
    3. 59:03
      Breaking Down Programming Paradigms: APL's Surprising Learning Curve // Aaron Hsu // Dyalog '17Dyalog User Meetings7.2K views • 9 years ago
    4. 7:48
      Conway's Game Of Life in APLDyalog236K views • 17 years ago
    5. 9:43
      A Sudoku Solver in APLDyalog47K views • 14 years ago
    6. 11:32
      Depth-first search in APLDyalog11K views • 12 years ago
    7. 2:03:12
      Co-dfns Live Stream: Compiler Design and ArchitectureAaron Hsu (arcfide)21K views • 9 years ago
    8. 58:36
      Advanced Topics in Programming Languages: A Lock-Free Hash TableGoogleTalksArchive29K views • 14 years ago
    9. 1:29:55
      Sorting Algorithms: Speed Is Found In The Minds of People - Andrei Alexandrescu - CppCon 2019CppCon184K views • 7 years ago
    10. 1:13:41
      CppCon 2014: Chandler Carruth "Efficiency with Algorithms, Performance with Data Structures"CppCon235K views • 12 years ago
    11. 38:38
      "Tree-sitter - a new parsing system for programming tools" by Max BrunsfeldStrange Loop Conference63K views • 8 years ago
    12. 59:34
      CppCon 2017: Matt Kulukundis “Designing a Fast, Efficient, Cache-friendly Hash Table, Step by Step”CppCon137K views • 9 years ago
    13. 1:14:52
      Effective Programs - 10 Years of Clojure - Rich HickeyClojureTV176K views • 9 years ago
    14. 1:19:57
      Simon Peyton Jones: Data Parallel HaskellnuACM28K views • 16 years ago
    15. 1:32:47
      Data-Oriented Demo: SOA, compositionJonathan Blow201K views • 11 years ago
    16. 34:55
      "Outperforming Imperative with Pure Functional Languages" by Richard FeldmanStrange Loop Conference98K views • 5 years ago
    17. 36:31
      Hey Underscore, You're Doing It Wrong!InfoQ141K views • 13 years ago
    18. 1:30:53
      C++Now 2018: You Can Do Better than std::unordered_map: New Improvements to Hash Table PerformanceCppNow63K views • 8 years ago
    19. 54:01
      Abseil's Open Source Hashtables: 2 Years In - Matt Kulukundis - CppCon 2019CppCon22K views • 7 years ago
    20. 1:07:41
      Modern Dictionaries by Raymond HettingerSF Python150K views • 9 years ago

    3 comments from Hacker News

    1. @jodrellblankJun 2021· in “Zig 0.8.0 Release Notes”

      > " his saves on allocations, saves on total memory usage " Co-Dfns is Aaron Hsu's project, and he has a talk[1] on a compiler implemented in a nano-pass style, once in Racket, once in Chez Scheme[2] and once in Dyalog APL, each using CPU and GPU. For compiling an AST with ~16 million nodes, he gives benchmark figures that Dyalog APL takes 64MB RAM to hold it, Racket takes 1051MB and Chez Scheme takes 1485MB. His provocative statement for the talk is "pointers are the refined sugar of programming". The APL version is 1/50th of the lines of code[4], runs typically 9x faster on the CPU, 50x-200x faster on the GPU, despite being interpreted by Dyalog vs compiled Scheme. There are benchmarks where the APL version loses in runtime, under 1k lines of code (which he calls "tiny tiny") so lots of startup overhead and not enough big arrays to gain ground on. He has one talk (available on YouTube) about his approach to using arrays to working with tree structures in a high-performance way in APL[3]. [1] [LINK] [2] he used to be on the Scheme R6RS steering committee, so he's not new/inexperienced with it [LINK] [3] this video [4] 17 lines of code which took a PhD researcher (him) 5-10 years to write, mind you.

      RecommendsView on HN
    2. @kadblasJun 2019· in “Why I think Haskell is the best general purpose language as of June 22 2019”

      Qualification: I was introduced to FP a number of years ago and have finally reached a point where I feel that I have a deep understanding of FP in general. In my mind, Haskell is the "best" language out there ("best" in that it provides the best overall gain when all tradeoffs are considered). I'm no longer confident that Haskell is the "best" language anymore. I was recently introduced to a language that might be even better than Haskell: Dyalog APL. ( [LINK] ). Try it out yourself ( [LINK] ) To explain why, I recommend watching Aaron Hsu's videos on Dyalog APL: - Does APL need a Type System? ( [LINK] ) - This is actually a very interesting question that is more nuanced than upon first glance. - Design Patterns and Anti-Patterns in APL ( [LINK] ) - The main takeaway from this video for me was the principle of "Idioms over libraries." - Higher Performance Tree-Wrangling, the APL way ( this video ) - Or how to model Trees without using pointers by using "Inverted Tables." (An inverted table is a table where the columns are the rows and the rows are the columns)

      RecommendsView on HN
    3. @snakyJan 2020· in “Language as an intellectual tool: From hieroglyphics to APL (1991)”

      I had this feeling exactly listening (great, as everything Aaron does) presentation about manipulation and transformation of trees in APL, this video

      RecommendsView on HN