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Thermal-Aware Scheduling: A Solution for Future Chip Multiprocessors Thermal Problems.

, and . DSD, page 123-126. IEEE Computer Society, (2006)

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Dynamic adaptive data structures for monitoring data streams., , , and . Data Knowl. Eng., 66 (1): 92-115 (2008)Preface., , , and . FPL, page xiii. IEEE, (2023)Heterogeneous- and NUMA-aware scheduling for many-core architectures., and . SYSTOR, page 2:1-2:12. ACM, (2017)ARADA: Adaptive Resource Allocation for Improving Energy Efficiency in Deep Learning Accelerators., , and . CF, page 63-72. ACM, (2023)Exploiting the Potential of Flexible Processing Units., , and . SBAC-PAD, page 34-45. IEEE, (2023)VEDLIoT: Next generation accelerated AIoT systems and applications., , , , , , , , , and 22 other author(s). CF, page 291-296. ACM, (2023)An Efficient Hybrid Deep Learning Accelerator for Compact and Heterogeneous CNNs., , and . ACM Trans. Archit. Code Optim., 21 (2): 25 (June 2024)LEGaTO: Low-Energy, Secure, and Resilient Toolset for Heterogeneous Computing., , , , , , , , , and 33 other author(s). DATE, page 169-174. IEEE, (2020)CacheFlow: A Short-Term Optimal Cache Management Policy for Data Driven Multithreading., , and . Euro-Par, volume 3149 of Lecture Notes in Computer Science, page 561-570. Springer, (2004)Evaluation of heterogeneous AIoT Accelerators within VEDLIoT., , , , , , , , , and 5 other author(s). DATE, page 1-6. IEEE, (2023)