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DLHub: Model and Data Serving for Science., , , , , , , , , and . IPDPS, page 283-292. IEEE, (2019)Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision., , , , , , , , , and 6 other author(s). BDCAT, page 15:1-15:10. ACM, (2023)Creating Training Data for Scientific Named Entity Recognition with Minimal Human Effort., , , , , , , , , and . ICCS (1), volume 11536 of Lecture Notes in Computer Science, page 398-411. Springer, (2019)Accelerating Communications in Federated Applications with Transparent Object Proxies., , , , , , , and . SC, page 59:1-59:15. ACM, (2023)DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies., , , , , , , , , and 82 other author(s). CoRR, (2023)RADICAL-Pilot and Parsl: Executing Heterogeneous Workflows on HPC Platforms., , , , , , and . WORKS@SC, page 27-34. IEEE, (2022)Not All Tasks Are Created Equal: Adaptive Resource Allocation for Heterogeneous Tasks in Dynamic Workflows., , , and . WORKS, page 17-24. IEEE, (2021)Towards a Hybrid Human-Computer Scientific Information Extraction Pipeline., , , , , , and . eScience, page 109-118. IEEE Computer Society, (2017)DLHub: Simplifying publication, discovery, and use of machine learning models in science., , , , , , , , , and 1 other author(s). J. Parallel Distributed Comput., (2021)Proxima: accelerating the integration of machine learning in atomistic simulations., , , , and . ICS, page 242-253. ACM, (2021)