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ReLeQ: A Reinforcement Learning Approach for Deep Quantization of Neural Networks., , , , and . CoRR, (2018)A Computational Stack for Cross-Domain Acceleration., , , , , , , and . HPCA, page 54-70. IEEE, (2021)Mixed-Signal Charge-Domain Acceleration of Deep Neural Networks through Interleaved Bit-Partitioned Arithmetic., , , , , , , and . PACT, page 399-411. ACM, (2020)In-Storage Domain-Specific Acceleration for Serverless Computing., , , , , , , , , and 1 other author(s). ASPLOS (2), page 530-548. ACM, (2024)Tandem Processor: Grappling with Emerging Operators in Neural Networks., , , , , , , , , and 2 other author(s). ASPLOS (2), page 1165-1182. ACM, (2024)VeriGOOD-ML: An Open-Source Flow for Automated ML Hardware Synthesis., , , , , , , , , and 6 other author(s). ICCAD, page 1-7. IEEE, (2021)Physically Accurate Learning-based Performance Prediction of Hardware-accelerated ML Algorithms., , , , , , , , , and 1 other author(s). MLCAD, page 119-126. ACM / IEEE, (2022)Glimpse: mathematical embedding of hardware specification for neural compilation., , and . DAC, page 1165-1170. ACM, (2022)MESA: Microarchitecture Extensions for Spatial Architecture Generation., , , , , , , , , and . ISCA, page 49:1-49:14. ACM, (2023)Restoring the Broken Covenant Between Compilers and Deep Learning Accelerators., , , , , , , , and . CoRR, (2023)