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    Clojure is Not Afraid of the GPU - Dragan Djuric

    ClojureTV

    1 HN recommender · recommended in 3 months, 2016–2018

    YouTube

    42:13 · 6.9K views · Nov 17, 2016

    Dragan Djuric presents Clojure libraries for GPU and numerical computing, including ClojureCL, ClojureCUDA and Neanderthal. He shows how a dynamic REPL workflow can be combined with low-level hardware acceleration for machine learning and data science.

    HN commenters point to it as the talk by the author of Neanderthal and the Clojure GPU libraries, including comparisons against the JVM and CPU.

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    3 comments from Hacker News

    1. @skardanMay 2017· in “Uncomplicate: Number crunching in Clojure”

      ClojureCUDA, ClojureCL (as in OpenCL) and Neanderthal are libraries developed by Dragan Djuric. Watch his talk from EuroClojure 2016 in Bratislava: this video

      RecommendsView on HN
    2. @thebeardedoneFeb 2018· in “Interactive GPU Programming, Part 2: Hello OpenCL”

      ClojureCL looks quite awesome, it looks like it takes all of the boiler plate out in comparison to C but I am very interested in the overhead. I tried aparapi for my bachelor thesis and for larger problems it seemed to have quite the overhead that the normal kernel did not have (several years ago). After watching your talk on youtube [1], I saw you compared the GPU implementation to the JVM and other CPU implementations in Clojure. Do you have any numbers for the same kernel being called from a native C openCL application? [1] this video

      CitesView on HN
    3. @tmpLispDec 2016· in “The Idea of Lisp”

      Data crunching on GPUs is a LISP strength. It runs code orders of magnitude faster than say python or c++. this video

      CitesView on HN