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| Name | Roadmap to Julia BLAS and LinearAlgebra | Chris Elrod | JuliaCon 2021 |
| Video Uploader | Video From The Julia Programming Language |
| Upload Date | This Video Uploaded At 29-07-2021 18:45:01 |
| Video Discription | This talk was given as part of JuliaCon 2021. Abstract: BLAS & LAPACK are integral components of many numerical algorithms. Due to their importance, a lot of effort has gone into optimizing ASM/C/Fortran implementations. Nonetheless, early work demonstrated that Julia's implementations were often faster than competitors while laying the groundwork for new routines specialized for new problems. We discuss a roadmap toward providing Julia BLAS and LAPACK libraries, from optimizations in LoopVectorization to libraries like Octavian and RecursiveFactorization. For more info on the Julia Programming Language, follow us on Twitter: https://twitter.com/JuliaLanguage and consider sponsoring us on GitHub: https://github.com/sponsors/JuliaLang Contents 00:00 Welcome! 00:09 Introduction 01:00 Why do we want to create Julia's version of BLAS and LAPACK? 03:03 Performance 03:40 Commentary on LoopVectorization.jl 04:50 Multi-threaded matrix multiplication 05:51 Our biggest success: RecursiveFactorization.jl 07:25 Multi-threaded implementations are not always straightforward 08:58 Recursive factorization is fast even for relatively big matrices 11:16 Flexibility 13:49 Express operation as BLAS, or optimize direct? 15:14 Interoperability with the rest of the Julia ecosystem 16:00 Support for a wide variety of types 16:47 Julia multi-threading can lead to better workload balance 18:43 Roadmap S/O to https://github.com/KZiemian for the video timestamps! Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/JuliaCommunity/YouTubeVideoTimestamps Interested in improving the auto generated captions? Get involved here: https://github.com/JuliaCommunity/YouTubeVideoSubtitles KQ8nvlURX4M |
| Category | Science & Technology |
| Tags | Julia | Language | Programming | programming | JuliaLang | coding | learn to code | Julia Language | ML | Machine Learning | anyone can code | tutorials | Julia programming | The Julia Programming Language |
