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Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision., , , , , , , , , and 6 other author(s). CoRR, (2024)QoS-aware edge AI placement and scheduling with multiple implementations in FaaS-based edge computing., , , , , and . Future Gener. Comput. Syst., (2024)Assessing the Current State of AWS Spot Market Forecastability., , , , , and . SuperCompCloud, page 8-15. IEEE, (2022)Balancing Federated Learning Trade-Offs for Heterogeneous Environments., , , and . PerCom Workshops, page 404-407. IEEE, (2023)Coding the Computing Continuum: Fluid Function Execution in Heterogeneous Computing Environments., , , , , , and . IPDPS Workshops, page 66-75. IEEE, (2021)Enhancing Automated FaaS with Cost-aware Provisioning of Cloud Resources., , and . e-Science, page 267-268. IEEE, (2021)ParaOpt: Automated Application Parameterization and Optimization for the Cloud., , , , , , , , , and . CloudCom, page 255-262. IEEE, (2019)Profiling and Predicting Application Performance on the Cloud., , , , , and . UCC, page 21-30. IEEE Computer Society, (2018)Tournament-Based Pretraining to Accelerate Federated Learning., , , , , and . SC Workshops, page 109-115. ACM, (2023)Unveiling Temporal Performance Deviation: Leveraging Clustering in Microservices Performance Analysis., , , , , , , , , and 2 other author(s). ICPE (Companion), page 72-76. ACM, (2024)