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Application-Driven Exascale: The JUPITER Benchmark Suite

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arxiv 2408.17211 v1 pith:DPMZTLSL submitted 2024-08-30 cs.DC cs.ARcs.PF

classification cs.DCcs.ARcs.PF
keywords benchmarkjupiterapplicationsexascalesuiteopenrequirementssoftware
verification ladder T0 review T1 audit T2 compute T3 formal

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Benchmarks are essential in the design of modern HPC installations, as they define key aspects of system components. Beyond synthetic workloads, it is crucial to include real applications that represent user requirements into benchmark suites, to guarantee high usability and widespread adoption of a new system. Given the significant investments in leadership-class supercomputers of the exascale era, this is even more important and necessitates alignment with a vision of Open Science and reproducibility. In this work, we present the JUPITER Benchmark Suite, which incorporates 16 applications from various domains. It was designed for and used in the procurement of JUPITER, the first European exascale supercomputer. We identify requirements and challenges and outline the project and software infrastructure setup. We provide descriptions and scalability studies of selected applications and a set of key takeaways. The JUPITER Benchmark Suite is released as open source software with this work at https://github.com/FZJ-JSC/jubench.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Introducing Milabench: Benchmarking Accelerators for AI

    cs.LG 2024-11 conditional novelty 6.0 of 10

    Mila releases Milabench, a 42-benchmark open-source suite, and shows that for real AI workloads the NVIDIA H100 generally outperforms AMD MI300X and Intel Gaudi2 despite MI300X's high synthetic FLOP counts.

  2. Energy-aware operation of HPC systems in Germany

    cs.DC 2024-11 conditional novelty 3.0 of 10

    This review of eight German HPC centers concludes that a combination of cooling, scheduling, monitoring, and hardware choices is required to meaningfully reduce energy use.

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