Bridging HPC Communities through the Julia Programming Language
Abstract
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 coordinated single-language and ecosystem paradigm and has a proven track record of achieving high performance without sacrificing user productivity. These aspects make Julia a viable alternative to high-performance computing's (HPC's) existing and increasingly costly many-body workflow composition strategy in which traditional HPC languages (e.g., Fortran, C, C++) are used for simulations, and higher-level languages (e.g., Python, R, MATLAB) are used for data analysis and interactive computing. Julia's rapid growth in language capabilities, package ecosystem, and community make it a promising universal language for HPC. This paper presents the views of a multidisciplinary group of researchers from academia, government, and industry that advocate for an HPC software development paradigm that emphasizes developer productivity, workflow portability, and low barriers for entry. We believe that the Julia programming language, its ecosystem, and its community provide modern and powerful capabilities that enable this group's objectives. Crucially, we believe that Julia can provide a feasible and less costly approach to programming scientific applications and workflows that target HPC facilities. In this work, we examine the current practice and role of Julia as a common, end-to-end programming model to address major challenges in scientific reproducibility, data-driven AI/machine learning, co-design and workflows, scalability and performance portability in heterogeneous computing, network communication, data management, and community education. As a result, the diversification of current investments to fulfill the needs of the upcoming decade is crucial as more supercomputing centers prepare for the exascale era.
Authors 12
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Massachusetts Institute of Technology
Affiliation as printed
Massachussetts Institute of Technology , USA
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Affiliation as printed
Oak Ridge National Laboratory , USA
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Affiliation as printed
Paderborn Center for Parallel Computing , Paderborn University , Germany
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Affiliation as printed
Department of Mathematics , University of Hamburg , Germany
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University of Stuttgart · Stuttgart Technical University of Applied Sciences · Computing Center · RWTH Aachen University
Affiliation as printed
Applied and Computational Mathematics , RWTH Aachen University , Germany
High-Performance Computing Center Stuttgart (HLRS) , University of Stuttgart , Germany
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Swiss Federal Institute for Forest, Snow and Landscape Research · ETH Zurich · Laboratory of Hydraulics, Hydrology and Glaciology
Affiliation as printed
Laboratory of Hydraulics, Hydrology and Glaciology (VAW) , ETH Zurich , Switzerland
Swiss Federal Institute for Forest , Snow and Landscape Research (WSL) , Birmensdorf , Switzerland
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Lawrence Berkeley National Laboratory · National Energy Research Scientific Computing Center
Affiliation as printed
National Energy Research Scientific Computing Center , Lawrence Berkeley National Laboratory , 1 Cyclotron Road , Berkeley , CA 94720 , USA
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Affiliation as printed
Centre for Advanced Research Computing , University College London , Gower Street , London , WC1E 6BT , United Kingdom
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Affiliation as printed
Swiss National Supercomputing Centre (CSCS) , ETH Zurich , Switzerland Computer Science and Artificial Intelligence Laboratory ,
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Affiliation as printed
Oak Ridge National Laboratory , USA
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Massachusetts Institute of Technology
Affiliation as printed
Massachussetts Institute of Technology , USA
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