About the webinar In 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 […]
Overview This interactive workshop is designed to provide a comprehensive introduction or refresher on the fundamental concepts of quantum computing, ensuring a solid foundation for participants to engage with the content of the Quantum Autumn School 2024. Target Audience This workshop is ideal for individuals who require a review of key quantum computing concepts, such […]
ENCCS joins forces again this year with NordIQuEst, to deliver a three-day quantum autumn school in early December 2024! The quantum autumn school will be held in Stockholm in hybrid form. About the Quantum Autumn School Experts from other organisations and industry will showcase the possibilities offered by quantum computing during the school. The school […]
Overview Welcome to the online workshop on Julia for High-Performance Scientific Computing on Dec. 9-12 (2024). In this four-half-day course, we will start with the basic features of Julia, and then delve into the specific topics on writing performant Julia code, multithreading, and distributed computing. Additionally, we will focus on Julia programming on HPC clusters […]
The 12th code of the month public session will be on December 11th, 2024 with a presentation by MaX CoE, about "SIESTA: a DFT code for large-scale computational material science in HPC environments" Please register using the link below.https://attendee.gotowebinar.com/register/2449943246926877273After registering, you will receive a confirmation email containing information about joining the webinar. Siesta and Computational Materials Science Computational materials science has experienced huge progress since the beginning […]
This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 951732. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and its associated countries .
