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Searching for Fast Model Families on Datacenter Accelerators.

, , , , , , and . CVPR, page 8085-8095. Computer Vision Foundation / IEEE, (2021)

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Training EfficientNets at Supercomputer Scale: 83% ImageNet Top-1 Accuracy in One Hour., , , , , , and . IPDPS Workshops, page 947-950. IEEE, (2021)ElasticFlow: A Complexity-Effective Approach for Pipelining Irregular Loop Nests., , , , and . ICCAD, page 78-85. IEEE, (2015)MobileDets: Searching for Object Detection Architectures for Mobile Accelerators., , , , , , , , , and . CVPR, page 3825-3834. Computer Vision Foundation / IEEE, (2021)Flushing-Enabled Loop Pipelining for High-Level Synthesis., , , and . DAC, page 76:1-76:6. ACM, (2014)An Energy-Efficient Branch Prediction with Grouped Global History., , , , and . ICPP, page 140-149. IEEE Computer Society, (2015)WOMD-LiDAR: Raw Sensor Dataset Benchmark for Motion Forecasting., , , , , , , , , and 5 other author(s). ICRA, page 4766-4773. IEEE, (2024)Towards the Co-design of Neural Networks and Accelerators., , , , , , , , , and . MLSys, mlsys.org, (2022)CASA: correlation-aware speculative adders., , , and . ISLPED, page 189-194. ACM, (2014)DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection., , , , , , , , , and 2 other author(s). CVPR, page 17161-17170. IEEE, (2022)Architecture and Synthesis for Area-Efficient Pipelining of Irregular Loop Nests., , , , and . IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 36 (11): 1817-1830 (2017)