The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Authors: Mosè Giordano (UCL), Rabab Alomairy (Massachusetts Institute of Technology (MIT)), William Godoy (Oak Ridge National Laboratory (ORNL)), Johannes Blaschke (ESnet; Lawrence Berkeley National Laboratory (LBNL)), Pedro Valero-Lara (Oak Ridge National Laboratory (ORNL)), Pengfei Ding (ESnet; Lawrence Berkeley National Laboratory (LBNL))
Abstract: The Julia for HPC BoF provides a place for the HPC community with interest in the Julia programming language as an LLVM front-end for science to close the gap between high-productivity languages and the performance of compiled languages. We invite participants from industry, government, and academia to discuss their experiences, identify and learn about opportunities and gaps. Topics include: community, adoption and support in HPC facilities, and new areas like quantum computing. The proposed fourth consecutive BoF continues the Julia for HPC working group’s engagement with the SC community, and complements the accepted tutorials on Julia for HPC at SC25.
Long Description: The open-source Julia programming language is rapidly gaining adoption in scientific computing. Building on Fortran’s legacy in numerical computing and large-scale simulations, Julia offers high-level abstractions for data analysis. HPC workflows for scientific discovery demand performance portability on heterogeneous systems, end-to-end co-design with advanced tuning tools, and large-scale data management. Julia addresses these through a unified approach that bridges the performance of C, C++, and Fortran (using MPI+X models) with the productivity of dynamic languages used in data analysis and AI. Its design emphasizes performance, reproducibility, and robust instrumentation, making it well-suited for modern HPC challenges and workflows.
This highly-interactive BoF targets the broader HPC community with interests in learning more about Julia as a viable HPC language. As well as discussing recent language and ecosystem developments which are relevant to the HPC community. For the first 25 minutes we invite a series of lighting talks to discuss their experiences using Julia for HPC. These talks will cover topics such as application development, Julia HPC software stack for CPU, GPU, network and data, support at supercomputing facilities, interoperability with existing HPC frameworks, and current efforts across supercomputing centers. For the rest of the session, we will encourage the participation of the audience to trigger discussion around these and other topics of relevance to the Julia HPC community.
There is a growing and enthusiastic multinational community of Julia users and developers on HPC systems (https://juliaparallel.org/resources/), reflected by broad support amongst many HPC centers (https://juliahpc.github.io/JuliaOnHPCClusters/user_hpcsystems/). Our BoF is international, multi-disciplinary, and multi-institutional, aiming to provide a platform for networking and idea exchange across different communities. We believe in the success of the proposed event, as similar Julia for HPC BoF experiences have been recently offered at SIAM PP, PASC, JuliaCon, and the U.S. Exascale Computing Project (2016-2023). Community interest in Julia is significant, enthusiastic, and growing, with the first edition of the Julia for HPC BoF at SC22 attracting approximately 70 attendees, and the second edition at SC23 (https://github.com/JuliaParallel/julia-hpc-bof-sc23) attracting over 100 attendees, while last year’s BoF at SC24 (https://github.com/JuliaParallel/julia-hpc-bof-sc24) attracted roughly 70 participants. Hence, the past few years have solidified the state of the BoF, while seeing a growing presence of Julia at SC in papers, tutorials, and posters sessions.
Prior BoFs at SC and JuliaCon conducted a user survey, giving a glimpse into the Julia for HPC community. We identified a growing trend where an increasing fraction of participants (53% – up from 42%) actively use Julia on HPC systems, at an increasing scale. This indicates strong, growing interest in the Julia language among the SC community, and still much opportunity for growth. This BoF is therefore well placed to engage with an evolving community of users. Most participants are working on simulation and modeling, data analysis, applied mathematics research, and more recently on novel topics such as quantum computing and AI. Moreover, there is a strong interest in developing codes that leverage GPUs, multi-threading, and multi-processing. Julia is becoming increasingly integral to these efforts, particularly in scientific software development.
Website: https://github.com/JuliaParallel/julia-hpc-bof-sc25