Back

Minisymposium Presentation

Enhancing GPU-Accelerated Scientific Computing in Julia with Ginkgo.jl

Wednesday, June 5, 2024
12:30
-
13:00
CEST
Climate, Weather and Earth Sciences
Climate, Weather and Earth Sciences
Climate, Weather and Earth Sciences
Chemistry and Materials
Chemistry and Materials
Chemistry and Materials
Computer Science and Applied Mathematics
Computer Science and Applied Mathematics
Computer Science and Applied Mathematics
Humanities and Social Sciences
Humanities and Social Sciences
Humanities and Social Sciences
Engineering
Engineering
Engineering
Life Sciences
Life Sciences
Life Sciences
Physics
Physics
Physics

Presenter

You
Wu
-
ETH Zurich

Computational Science and Engineering (CSE) student and team member of the student HPC team RACKlette at ETH Zürich.

Description

Solving sparse linear systems on GPU-accelerated systems efficiently is a highly specialized and demanding task. The implementation of efficient solvers incorporates not only deep insights into the problem but also an extensive understanding of the underlying hardware and the respective platform-specific languages. This interdisciplinary orchestration poses significant challenges in scientific software development.

This talk presents recent developments on Ginkgo.jl, a Julia wrapper package of the modern C++-based sparse linear algebra library Ginkgo. We demonstrate its performance through a series of benchmarks and showcase an example where we solve the sparse linear system assembled from the finite element toolbox package, Ferrite.jl, using a preconditioned iterative solver. We highlight its interoperability with existing packages in the Julia package ecosystem.

Authors