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DTSTART;TZID=Europe/Stockholm:20231002T090000
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SUMMARY:Julia for High Performance Data Analysis
DESCRIPTION:Julia is a modern high-level programming language that is fast (on par with traditional HPC languages like Fortran and C) and relatively easy to write like Python or Matlab. It thus solves the “two-language problem”\, i.e. when prototype code in a high-level language needs to be combined with or rewritten in a lower-level language to improve performance. \n\n\n\nAlthough Julia is a general-purpose language\, many of its features are particularly useful for numerical scientific computation\, and a wide range of both domain-specific and general libraries are available for statistics\, machine learning and numerical modelling. \n\n\n\nThis online workshop will start by briefly covering the basics of Julia’s syntax and features\, and then introduce methods and libraries which are useful for writing high-performance code for modern HPC systems. After attending the workshop\, you will: \n\n\n\n\nBe comfortable with Julia’s syntax\, in-built package manager\, and development tools.\n\n\n\nUnderstand core language features like its type system\, multiple dispatch\, and composability.\n\n\n\nBe able to write your own Julia packages from scratch.\n\n\n\nKnow how to perform various linear algebra analysis on datasets.\n\n\n\nBe productive in analysing and visualising large datasets in Julia using dataframes and visualisation packages.\n\n\n\nBe familiar with several Julia libraries for visualisation and machine learning.\n\n\n\nUnderstand how to analyse large datasets efficiently in Julia using statistical methods.\n\n\n\n\nPrerequisites\n\n\n\n\nExperience in one or more programming languages.\n\n\n\nFamiliarity with basic concepts in linear algebra and machine learning.\n\n\n\nBasic experience with working in a terminal is also beneficial. \n\n\n\nParticipants are expected to install Julia\, VSCode and Zoom before the workshop starts\n\n\n\n\nTentative agenda\n\n\n\nDay 1  \n\n\n\nIntroduction to Julia syntax and features. \n\n\n\nDay 2 \n\n\n\nJulia for data analysis\, data frames\, visualization\, various data formats\, read/write data\, missing data. \n\n\n\nLinear algebra\, array matrix and vector operations\, performance comparisons\, random matrices\, sparse matrices\, eigenvalues/eigenvectors and PCA. \n\n\n\nDay 3 \n\n\n\nClustering\, classification\, machine learning\, deep learning.  \n\n\n\nDay 4 \n\n\n\nRegression\, time series analysis and prediction. \n\n\n\nRegistration\n\n\n\nRegistrations are now closed. \n\n\n\nDisclaimer\n\n\n\nThis training is intended for users established in the European Union or a country associated with Horizon 2020. You can read more about the countries associated with Horizon2020 here https://ec.europa.eu/info/research-and-innovation/statistics/framework-programme-facts-and-figures/horizon-2020-country-profiles_e
URL:https://enccs.se/events/10-2023-julia-for-hpda/
LOCATION:Online
CATEGORIES:ENCCS Event
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DTSTART;TZID=Europe/Stockholm:20231010T090000
DTEND;TZID=Europe/Stockholm:20231013T120000
DTSTAMP:20260422T191959
CREATED:20230628T094101Z
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SUMMARY:Julia for High-Performance Scientific Computing
DESCRIPTION:Register\n\n\n\n\n\n\n\n\n\n\nJulia is a modern high-level programming language that is fast (on par with traditional HPC languages like Fortran and C) and relatively easy to write like Python or Matlab. It thus solves the “two-language problem”\, i.e. when prototype code in a high-level language needs to be combined with or rewritten in a lower-level language to improve performance. \n\n\n\nAlthough Julia is a general-purpose language\, many of its features are particularly useful for numerical scientific computation\, and a wide range of both domain-specific and general libraries are available for numerical modelling and simulation. \n\n\n\nThe language supports parallelization for both shared-memory and distributed HPC architectures\, and native Julia libraries are available for running on GPUs from different vendors. \n\n\n\nThis online workshop will start by briefly covering the basics of Julia’s syntax and features\, and then introduce methods and libraries which are useful for writing high-performance code for modern HPC systems. After attending the workshop you will:  \n\n\n\n\nBe comfortable with Julia’s syntax\, in-built package manager\, and development tools.\n\n\n\nUnderstand core language features like its type system\, multiple dispatch\, and composability.\n\n\n\nBe able to write your own Julia packages from scratch.\n\n\n\nHave an overview of Julia’s parallelization and GPU-porting strategies and the know-how to get started using them.\n\n\n\nBe familiar with crucial Julia libraries for scientific modelling\, visualization\, and machine learning.\n\n\n\n\nPrerequisites\n\n\n\nThe workshop is intended for researchers who are familiar with one or more other languages like Python\, R\, Matlab\, C/C++ or Fortran but would like to learn an exciting modern high-performance language. \n\n\n\nBasic experience with working in a terminal is also beneficial. Participants are expected to install Julia\, VSCode and Zoom before the workshop starts. \n\n\n\nPreliminary Agenda\n\n\n\nDay 1  \n\n\n\nTime (CEST)Time (EEST)Section9:30-10:3010:30-11:30Welcome and Motivation10:30-11:0011:30-12:00Julia syntax11:00-11:3012:00-12:30Special Julia features11:30-12:3012:30-13:30Break12:30-13:0013:30-14:00Special Julia features13:00-14:0014:00-15:00Developing in Julia14:00-14:1015:00-15:10Package ecosystem14:10-14:3015:10-15:30Buffer time\, Q&A\n\n\n\nDay 2 \n\n\n\nTime (CEST)Time (EEST)Section9:30-10:0010:30-11:00Welcome and Motivation10:00-11:3011:00-12:30Writing performant Julia code11:30-12:3012:30-13:30Break12:30-13:3013:30-14:30Multithreading13:30-14:3014:30-15:30Distributed\n\n\n\nDay 3 \n\n\n\nTime (CEST)Time (EEST)Section9:30-10:3010:30-11:30Dagger10:30-11:3011:30-12:30Running on HPC11:30-12:3012:30-13:30Break12:30-13:3013:30-14:30MPI13:30-14:3014:30-15:30Buffer time\n\n\n\nDay 4 \n\n\n\nTime (CEST)Time (EEST)Section9:30-11:0010:30-12:30GPU computing11:30-12:3012:30-13:30Break12:30-13:3013:30-14:30Interfacing to C\, Fortran and Python13:30-14:1514:30-15:15Advanced exercises14:15-14:3015:15-15:30Conclusions and outlook\n\n\n\nRegistration\n\n\n\nPlease register by following the link https://events.prace-ri.eu/event/1512/registrations/1104/. \n\n\n\nDisclaimer\n\n\n\nThis training is intended for users established in the European Union or a country associated with Horizon 2020. You can read more about the countries associated with Horizon2020 here https://ec.europa.eu/info/research-and-innovation/statistics/framework-programme-facts-and-figures/horizon-2020-country-profiles_e
URL:https://enccs.se/events/10-2023-julia-for-hpc/
LOCATION:Online
CATEGORIES:ENCCS Event
ATTACH;FMTTYPE=image/jpeg:https://media.enccs.se/2023/06/julia-for-hpc-enccs-csc.jpg
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