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Restoring the Broken Covenant Between Compilers and Deep Learning Accelerators., , , , , , , , and . CoRR, (2023)Glimpse: mathematical embedding of hardware specification for neural compilation., , and . DAC, page 1165-1170. ACM, (2022)Planaria: Dynamic Architecture Fission for Spatial Multi-Tenant Acceleration of Deep Neural Networks., , , , , , , , , and 2 other author(s). MICRO, page 681-697. IEEE, (2020)AI for Optimized Execution of AI. University of California, San Diego, USA, (2022)Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation., , , and . ICLR, OpenReview.net, (2020)Ordering Chaos: Memory-Aware Scheduling of Irregularly Wired Neural Networks for Edge Devices., , , , , and . MLSys, mlsys.org, (2020)Data Motion Acceleration: Chaining Cross-Domain Multi Accelerators., , , , , , , , and . HPCA, page 1043-1062. IEEE, (2024)Reinforcement Learning and Adaptive Sampling for Optimized DNN Compilation., , and . CoRR, (2019)Tandem Processor: Grappling with Emerging Operators in Neural Networks., , , , , , , , , and 2 other author(s). ASPLOS (2), page 1165-1182. ACM, (2024)In-Storage Domain-Specific Acceleration for Serverless Computing., , , , , , , , , and 1 other author(s). ASPLOS (2), page 530-548. ACM, (2024)