22 citations · 120 across the 9 of their papers we have counts for
10 papers
Automated Translation and Accelerated Solving of Differential Equations on Multiple GPU Platforms
Utkarsh Utkarsh, Valentin Churavy, Yingbo Ma +8
We demonstrate a high-performance vendor-agnostic method for massively parallel solving of ensembles of ordinary differential equations (ODEs) and stochastic differential equations…
Evaluating performance and portability of high-level programming models: Julia, Python/Numba, and Kokkos on exascale nodes
William F. Godoy, Pedro Valero-Lara, T. Elise Dettling +7
We explore the performance and portability of the high-level programming models: the LLVM-based Julia and Python/Numba, and Kokkos on high-performance computing (HPC) nodes: AMD Ep…
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…
Bring the BitCODE -- Moving Compute and Data in Distributed Heterogeneous Systems
Wenbin Lu, Luis E. Peña, Pavel Shamis +3
In this paper, we present a framework for moving compute and data between processing elements in a distributed heterogeneous system. The implementation of the framework is based on…
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…
Batched Second-Order Adjoint Sensitivity for Reduced Space Methods
François Pacaud, Michel Schanen, Daniel Adrian Maldonado +4
This paper presents an efficient method for extracting the second-order sensitivities from a system of implicit nonlinear equations on upcoming graphical processing units (GPU) dom…
Large-eddy simulations with ClimateMachine: a new open-source code for atmospheric simulations on GPUs and CPUs
Akshay Sridhar, Yassine Tissaoui, Simone Marras +11
We introduce ClimateMachine, a new open-source atmosphere modeling framework using the Julia language to be performance portable on central processing units (CPUs) and graphics pro…
Instead of Rewriting Foreign Code for Machine Learning, Automatically Synthesize Fast Gradients
William S. Moses, Valentin Churavy
Applying differentiable programming techniques and machine learning algorithms to foreign programs requires developers to either rewrite their code in a machine learning framework,…
Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs
Liu Yang, Sean Treichler, Thorsten Kurth +8
Uncertainty quantification for forward and inverse problems is a central challenge across physical and biomedical disciplines. We address this challenge for the problem of modeling…
Dynamic Automatic Differentiation of GPU Broadcast Kernels
Jarrett Revels, Tim Besard, Valentin Churavy +2
We show how forward-mode automatic differentiation (AD) can be employed within larger reverse-mode computations to dynamically differentiate broadcast operations in a GPU-friendly…