activity
20162025
most citedUncertainty propagation with functionally correlated quantities

22 citations · 57 across the 6 of their papers we have counts for

collaborators

6 papers

cs.MS2025

Accuracy of Mathematical Functions in Julia

Mantas Mikaitis, Mosè Giordano, Tejaswa Rizyal

Basic computer arithmetic operations, such as , , or are correctly rounded, whilst mathematical functions such as , , or in general are not, m…

cs.DC2025

Extrae.jl: Julia bindings for the Extrae HPC Profiler

Sergio Sanchez-Ramirez, Mosè Giordano

The Julia programming language has gained acceptance within the High-Performance Computing (HPC) community due to its ability to tackle two-language problem: Julia code feels as hi…

cs.DC2022★ 19 cited

Bridging HPC Communities through the Julia Programming Language

Valentin Churavy, William F Godoy, Carsten Bauer +9

The Julia programming language has evolved into a modern alternative to fill existing gaps in scientific computing and data science applications. Julia leverages a unified and coor…

cs.DC2022★ 14 cited

Productivity meets Performance: Julia on A64FX

Mosè Giordano, Milan Klöwer, Valentin Churavy

The Fujitsu A64FX ARM-based processor is used in supercomputers such as Fugaku in Japan and Isambard 2 in the UK and provides an interesting combination of hardware features such a…

astro-ph.IM2018★ 2 cited

Towards new solutions for scientific computing: the case of Julia

Maurizio Tomasi, Mosè Giordano

This year marks the consolidation of Julia (https://julialang.org/), a programming language designed for scientific computing, as the first stable version (1.0) has been released,…

physics.data-an2016★ 22 cited

Uncertainty propagation with functionally correlated quantities

Mosè Giordano

Many uncertainty propagation software exist, written in different programming languages, but not all of them are able to handle functional correlation between quantities. In this p…