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PipeEdge: Pipeline Parallelism for Large-Scale Model Inference on Heterogeneous Edge Devices., , , , , , and . DSD, page 298-307. IEEE, (2022)Quantpipe: Applying Adaptive Post-Training Quantization For Distributed Transformer Pipelines In Dynamic Edge Environments., , , , , and . ICASSP, page 1-5. IEEE, (2023)CoPPer: Soft Real-Time Application Performance Using Hardware Power Capping., , , and . ICAC, page 31-41. IEEE, (2019)QuantPipe: Applying Adaptive Post-Training Quantization for Distributed Transformer Pipelines in Dynamic Edge Environments., , , , , and . CoRR, (2022)Distributed Edge Machine Learning Pipeline Scheduling with Reverse Auctions., , and . FMEC, page 196-203. IEEE, (2023)Evaluating Deep Learning Recommendation Model Training Scalability with the Dynamic Opera Network., , , , , and . EuroMLSys@EuroSys, page 169-175. ACM, (2024)Distributed and Heterogeneous SAR Backprojection with Halide., , , , and . HPEC, page 1-9. IEEE, (2021)Compiler Abstractions and Runtime for Extreme-scale SAR and CFD Workloads., , , , , and . ESPM2@SC, page 1-7. IEEE, (2020)Proteus: Language and Runtime Support for Self-Adaptive Software Development., , , , , , , , , and 9 other author(s). IEEE Software, 36 (2): 73-82 (2019)Pipeline Parallelism for Inference on Heterogeneous Edge Computing., , , , , , and . CoRR, (2021)