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Data Placement Optimization in GPU Memory Hierarchy using Predictive Modeling., , , and . MCHPC@SC, page 45-49. ACM, (2018)HPCFAIR: Enabling FAIR AI for HPC Applications., , , , , , and . MLHPC@SC, page 58-68. IEEE, (2021)HPC Ontology: Towards a Unified Ontology for Managing Training Datasets and AI Models for High-Performance Computing., , , , , , and . MLHPC@SC, page 69-80. IEEE, (2021)Is Data Placement Optimization Still Relevant on Newer GPUs?, , , , , and . PMBS@SC, page 83-96. IEEE, (2018)Bootstrapping Parameter Space Exploration for Fast Tuning., , , , , , , , , and . ICS, page 385-395. ACM, (2018)MPI Stages: Checkpointing MPI State for Bulk Synchronous Applications., , , , , and . EuroMPI, page 13:1-13:11. ACM, (2018)MLPerf™ HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems., , , , , , , , , and 33 other author(s). MLHPC@SC, page 33-45. IEEE, (2021)Mapping Medley: Adaptive Parallelism Mapping with Varying Optimization Goals.. LCPC, volume 10136 of Lecture Notes in Computer Science, page 299-313. Springer, (2016)Change Detection Based Parallelism Mapping: Exploiting Offline Models and Online Adaptation., and . LCPC, volume 8967 of Lecture Notes in Computer Science, page 208-223. Springer, (2014)Smart, adaptive mapping of parallelism in the presence of external workload., , and . CGO, page 13:1-13:10. IEEE Computer Society, (2013)