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SUMMARY:GPU programming using Julia - A practical intro webinar
DESCRIPTION:Registrations are closed for this event. \n\n\n\n\n\nAbout the webinar\n\n\n\nIn this webinar\, we focus on GPU-accelerated computing with Julia\, one of the most popular high-level\, general-purpose dynamic programming languages for science\, engineering\, data analytics\, and deep learning applications. Starting from the basic syntax of Julia\, we will span topics on multiple-dispatch paradigm\, metaprogramming\, and then additional special features of Julia for classic machine learning and deep learning\, with a focus on their unique features and capabilities for high-performance computing. \n\n\n\nIn the past decade\, Graphics Processing Units (GPUs) have ignited the dynamic evolution of data science. But GPUs can do a lot more than machine learning – these powerful devices can accelerate and massively parallelise any general-purpose computational load in domains involving big data and heavy number crunching. You can use the GPU in your personal computer\, or scale up your application to run on a supercomputer. How can you get started? \n\n\n\nWho is the webinar for?\n\n\n\nThe GPU programming using Julia webinar is for data scientists\, software developers and researchers who are: \n\n\n\n\nalready familiar with one or more programming languages (Python\, R\, C/C++\, Fortran\, Matlab\,…) but want to add a new exciting high-level yet performant language to their repertoire\,\n\n\n\nneed to analyze big data or perform computationally demanding modelling or analyses\,\n\n\n\nmight be mixing a high-level and a low-level language for performance reasons but want to make their life easier.\n\n\n\n\nKey takeaways\n\n\n\nAfter attending this seminar\, you will be able to: \n\n\n\n\nBe familiar with several Julia libraries for scientific modelling\, visualization\, and machine learning\n\n\n\nHave an overview of Julia’s parallelization and GPU-porting strategies and the know-how to start using them\n\n\n\nMake informed decisions about your GPU workflows\n\n\n\n\nLesson material\n\n\n\nThe ENCCS Practical Intro webinar series aims to provide concise and condensed introductions to key topics in high-performance computing and related technologies. Webinar materials\, such as notebooks and code examples\, are made available online on GitHub. \n\n\n\nFor more thorough tutorials and self-study materials\, please visit the library of ENCCS lessons (https://enccs.se/lessons/). \n\n\n\nSpeakers\n\n\n\n\nFrancesco Fiusco (RISE/ENCCS)\n\n\n\nYonglei Wang (LiU/ENCCS)\n\n\n\n\nRegistration\n\n\n\nRegister by visiting this link https://events.prace-ri.eu/event/1580/registrations/1142/ \n\n\n\n\n\n\n\nRestrictions\n\n\n\nDue to EuroCC2 regulations\, we CAN NOT ACCEPT generic or private email addresses. Please use your official university or company email address for registration. \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/gpu-programming-using-julia-a-practical-intro-webinar/
LOCATION:Online
CATEGORIES:ENCCS Event
ATTACH;FMTTYPE=image/webp:https://media.enccs.se/2024/10/GPU-programming-julia.webp
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