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Julia as a unifying end-to-end workflow language on the Frontier exascale system...

Publication Type
Conference Paper
Book Title
SC-W 2023: Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis
Publication Date
Page Numbers
1989 to 1999
Publisher Location
New York, New York, United States of America
Conference Name
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Conference Location
Denver, Colorado, United States of America
Conference Sponsor
IEEE Computer Society, ACM, SIGHPC, TCHPC
Conference Date

We evaluate Julia as a single language and ecosystem paradigm powered by LLVM to develop workflow components for high-performance computing. We run a Gray-Scott, 2-variable diffusion-reaction application using a memory-bound, 7-point stencil kernel on Frontier, the US Department of Energy’s first exascale supercomputer. We evaluate the performance, scaling, and trade-offs of (i) the computational kernel on AMD’s MI250x GPUs, (ii) weak scaling up to 4,096 MPI processes/GPUs or 512 nodes, (iii) parallel I/O writes using the ADIOS2 library bindings, and (iv) Jupyter Notebooks for interactive analysis. Results suggest that although Julia generates a reasonable LLVM-IR, a nearly 50% performance difference exists vs. native AMD HIP stencil codes when running on the GPUs. As expected, we observed near-zero overhead when using MPI and parallel I/O bindings for system-wide installed implementations. Consequently, Julia emerges as a compelling high-performance and high-productivity workflow composition language, as measured on the fastest supercomputer in the world.