Scalable Architecture-Agnostic Finite Differences with Chmy.jl
The Julia Programming Language via YouTube
Lead AI-Native Products with Microsoft's Agentic AI Program
Launch Your Cybersecurity Career in 6 Months
Overview
Google, IBM & Meta Certificates – 40% Off
One plan covers every Professional Certificate on Coursera.
Unlock All Certificates
Explore Chmy.jl, a Julia package designed for developing scalable finite-difference solvers that prioritize portability, ease of use, and minimal computational overhead in this 11-minute conference talk. Learn about the package's comprehensive modules for working with structured staggered grids, discrete fields, finite-difference and interpolation operators, boundary conditions, and distributed computing capabilities. Discover how Chmy.jl enables users to write functions that execute seamlessly on both CPUs and GPUs supported by the JuliaGPU ecosystem, making it an architecture-agnostic solution for computational problems. Gain insights into the design principles and practical applications of this tool for scientific computing and numerical analysis, presented by Ivan Utkin at JuliaCon Local Paris 2025.
Syllabus
Scalable architecture-agnostic finite differences with Chmy.jl | Utkin | Paris 2025
Taught by
The Julia Programming Language