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Utilization-Based Scheduling of Flexible Mixed-Criticality Real-Time Tasks.

, , , , , , and . IEEE Trans. Computers, 67 (4): 543-558 (2018)

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Combining process splitting and merging transformations for Polyhedral Process Networks., , and . ESTIMedia, page 97-106. IEEE Computer Society, (2010)System-level scheduling of real-time streaming applications using a semi-partitioned approach., , and . DATE, page 1-6. European Design and Automation Association, (2014)Mapping of streaming applications considering alternative application specifications., , and . ACM Trans. Embed. Comput. Syst., 12 (1s): 34:1-34:21 (2013)On the hard-real-time scheduling of embedded streaming applications., and . Des. Autom. Embed. Syst., 17 (2): 221-249 (2013)Energy-Efficient and High-Throughput CNN Inference on Embedded CPUs-GPUs MPSoCs., , and . SAMOS, volume 13227 of Lecture Notes in Computer Science, page 127-143. Springer, (2021)On compile-time evaluation of process partitioning transformations for Kahn process networks., , and . CODES+ISSS, page 31-40. ACM, (2009)EDF-VD Scheduling of Mixed-Criticality Systems with Degraded Quality Guarantees., , , , , , and . RTSS, page 35-46. IEEE Computer Society, (2016)An accurate energy model for streaming applications mapped on MPSoC platforms., and . ICSAMOS, page 205-212. IEEE, (2013)Energy-Efficient Scheduling of Real-Time Tasks on Heterogeneous Multicores Using Task Splitting., , , and . RTCSA, page 149-158. IEEE Computer Society, (2016)NimbleAI: Towards Neuromorphic Sensing-Processing 3D-integrated Chips., , , , , , , , , and 39 other author(s). DATE, page 1-6. IEEE, (2023)