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Inference-Optimized AI and High Performance Computing for Gravitational Wave Detection at Scale.

, , , , and . Frontiers Artif. Intell., (2022)

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AI ensemble for signal detection of higher order gravitational wave modes of quasi-circular, spinning, non-precessing binary black hole mergers., , and . CoRR, (2023)HDF5 Cache VOL: Efficient and Scalable Parallel I/O through Caching Data on Node-local Storage., , , , , , and . CCGRID, page 61-70. IEEE, (2022)Interpretable AI forecasting for numerical relativity waveforms of quasi-circular, spinning, non-precessing binary black hole mergers., , and . CoRR, (2021)Atomic Defect Identification with Sparse Sampling and Deep Learning., , , , , and . SMC, volume 1512 of Communications in Computer and Information Science, page 455-463. Springer, (2021)Performance Portability Evaluation of OpenCL Benchmarks across Intel and NVIDIA Platforms., , , , , , , , , and . IPDPS Workshops, page 330-339. IEEE, (2020)Physics-inspired spatiotemporal-graph AI ensemble for gravitational wave detection., , and . CoRR, (2023)DLIO: A Data-Centric Benchmark for Scientific Deep Learning Applications., , , , and . CCGRID, page 81-91. IEEE, (2021)Stimulus: Accelerate Data Management for Scientific AI applications in HPC., , , , and . CCGRID, page 109-118. IEEE, (2022)Inference-Optimized AI and High Performance Computing for Gravitational Wave Detection at Scale., , , , and . Frontiers Artif. Intell., (2022)