A Fast and Flexible CFD Solver with Heterogeneous Execution - JuliaCon 2024
Offered By: The Julia Programming Language via YouTube
Course Description
Overview
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore a conference talk from JuliaCon 2024 that delves into the evolution of WaterLily.jl, a computational fluid dynamics solver in Julia. Learn how this CFD solver transitioned from a serial-CPU implementation to a backend-agnostic solution capable of seamless execution across multi-threaded CPUs and various GPU vendors. Discover the meta-programming approach used to generalize array iterator implementation and the utilization of KernelAbstractions.jl for architecture-specific kernel specialization. Examine performance comparisons showing WaterLily.jl matching state-of-the-art CFD solvers written in C++ or Fortran in single-GPU tests. Gain insights into the potential integration of machine learning models and differentiability into the solver, expanding its capabilities for future applications.
Syllabus
A fast and flexible CFD solver with heterogeneous execution | Weymouth, Font | JuliaCon 2024
Taught by
The Julia Programming Language
Related Courses
Моделирование биологических молекул на GPU (Biomolecular modeling on GPU)Moscow Institute of Physics and Technology via Coursera LLM Server
Pragmatic AI Labs via edX AI Infrastructure and Operations Fundamentals
Nvidia via Coursera Open Source LLMOps Solutions
Duke University via Coursera Deep Learning - Computer Vision for Beginners Using PyTorch
Packt via Coursera