{"paper":{"title":"GPU Performance of an Entropy-Stable Discontinuous Galerkin Euler Solver with Non-Conservative Terms","license":"http://creativecommons.org/licenses/by/4.0/","headline":"Entropy-stable discontinuous Galerkin solver for Euler equations with buoyancy reaches nearly 70% of GPU peak performance.","cross_cats":["cs.NA"],"primary_cat":"math.NA","authors_text":"Francis X. Giraldo, Henry Waterhouse, Lucas C. Wilcox, Maciej Waruszewski","submitted_at":"2026-05-15T22:43:11Z","abstract_excerpt":"The entropy-stable discontinuous Galerkin method for compressible Euler equations with buoyancy is implemented on graphics processing unit (GPU) hardware. We measure the performance of the solver on three-dimensional problems: the rising thermal bubble and the baroclinic instability in a channel. On NVIDIA A100 hardware, the solver achieves nearly 70\\% of 64-bit floating-point peak performance for the most computationally expensive kernel (volume terms) and significantly reduces the computational overhead typically incurred by two point entropy-stable fluxes in the volume terms. We also presen"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"On NVIDIA A100 hardware, the solver achieves nearly 70% of 64-bit floating-point peak performance for the most computationally expensive kernel (volume terms) ... factor of 10× faster and better than 13× more energy efficient than the CPU code ... extend symmetry-based flux savings to the non-symmetric gravity term, preserving nearly the full factor-of-two speedup.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The sequence of GPU-specific modifications (reduced complex operations, lower memory traffic, load balancing) preserves both the formal entropy stability and the numerical accuracy of the original discontinuous Galerkin scheme when non-conservative buoyancy terms are present.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"GPU port of entropy-stable DG Euler solver with non-conservative buoyancy terms reaches nearly 70% of 64-bit peak on A100 volume kernels, delivers 10x speedup and 13x better energy efficiency versus CPU, and preserves symmetry-based flux savings.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"Entropy-stable discontinuous Galerkin solver for Euler equations with buoyancy reaches nearly 70% of GPU peak performance.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"f21034abbecdd57fff2064be8f2721683f5ebdea0c466c032452681f7870a1c1"},"source":{"id":"2605.16684","kind":"arxiv","version":1},"verdict":{"id":"2b4532db-23a6-4a22-9432-8d7060925633","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-19T20:34:31.502373Z","strongest_claim":"On NVIDIA A100 hardware, the solver achieves nearly 70% of 64-bit floating-point peak performance for the most computationally expensive kernel (volume terms) ... factor of 10× faster and better than 13× more energy efficient than the CPU code ... extend symmetry-based flux savings to the non-symmetric gravity term, preserving nearly the full factor-of-two speedup.","one_line_summary":"GPU port of entropy-stable DG Euler solver with non-conservative buoyancy terms reaches nearly 70% of 64-bit peak on A100 volume kernels, delivers 10x speedup and 13x better energy efficiency versus CPU, and preserves symmetry-based flux savings.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"The sequence of GPU-specific modifications (reduced complex operations, lower memory traffic, load balancing) preserves both the formal entropy stability and the numerical accuracy of the original discontinuous Galerkin scheme when non-conservative buoyancy terms are present.","pith_extraction_headline":"Entropy-stable discontinuous Galerkin solver for Euler equations with buoyancy reaches nearly 70% of GPU peak performance."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.16684/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"doi_title_agreement","ran_at":"2026-05-19T21:01:19.296582Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"doi_compliance","ran_at":"2026-05-19T20:41:38.752340Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"claim_evidence","ran_at":"2026-05-19T19:01:56.379484Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"ai_meta_artifact","ran_at":"2026-05-19T18:33:26.499807Z","status":"skipped","version":"1.0.0","findings_count":0}],"snapshot_sha256":"da07ce307f2a403755579c734aeffc70a2aefadeedd612f19a4719f824fab52b"},"references":{"count":297,"sample":[{"doi":"10.1137/1.9781611976199","year":null,"title":"Betts, John T. , year =. 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