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Exploiting Dynamic Thermal Energy Harvesting for Reusing in Smartphone with Mobile Applications.

, , , , and . ASPLOS, page 243-256. ACM, (2018)

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Exploiting Dynamic Thermal Energy Harvesting for Reusing in Smartphone with Mobile Applications., , , , and . ASPLOS, page 243-256. ACM, (2018)Towards sustainable in-situ server systems in the big data era., , , , , , , and . ISCA, page 14-26. ACM, (2015)Bridging the Semantic Gaps of GPU Acceleration for Scale-out CNN-based Big Data Processing: Think Big, See Small., , , , , , and . PACT, page 315-326. ACM, (2016)Towards Pervasive and User Satisfactory CNN across GPU Microarchitectures., , , and . HPCA, page 1-12. IEEE Computer Society, (2017)LerGAN: A Zero-Free, Low Data Movement and PIM-Based GAN Architecture., , , , and . MICRO, page 669-681. IEEE Computer Society, (2018)High-Quality 3-D InISAR Imaging of Maneuvering Target Based on a Combined Processing Approach., , , , and . IEEE Geosci. Remote. Sens. Lett., 10 (5): 1036-1040 (2013)Towards "Full Containerization" in Containerized Network Function Virtualization., , and . ASPLOS, page 467-481. ACM, (2017)Eager pruning: algorithm and architecture support for fast training of deep neural networks., , , and . ISCA, page 292-303. ACM, (2019)Scheduling Tasks with Mixed Timing Constraints in GPU-Powered Real-Time Systems., , , , , , and . ICS, page 30:1-30:13. ACM, (2016)CoExe: An Efficient Co-execution Architecture for Real-Time Neural Network Services., , , , , , and . DAC, page 1-6. IEEE, (2020)