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PlaidML-HE: Acceleration of Deep Learning Kernels to Compute on Encrypted Data.

, , , and . ICCD, page 333-336. IEEE, (2019)

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nGraph-HE: a graph compiler for deep learning on homomorphically encrypted data., , , and . CF, page 3-13. ACM, (2019)Protecting the supply chain for automotives and IoTs., , and . DAC, page 89:1-89:4. ACM, (2018)FHEmem: A Processing In-Memory Accelerator for Fully Homomorphic Encryption., , , , , , , , , and . CoRR, (2023)Tolerating Defects in Low-Power Neural Network Accelerators Via Retraining-Free Weight Approximation., , , , and . ACM Trans. Embed. Comput. Syst., 20 (5s): 85:1-85:21 (2021)PlaidML-HE: Acceleration of Deep Learning Kernels to Compute on Encrypted Data., , , and . ICCD, page 333-336. IEEE, (2019)Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims., , , , , , , , , and 49 other author(s). CoRR, (2020)Domain-specific Accelerators for Ideal Lattice-based Public Key Protocols., , , and . IACR Cryptol. ePrint Arch., (2018)Exploring Energy Efficient Architectures for RLWE Lattice-Based Cryptography., , , and . J. Signal Process. Syst., 93 (10): 1139-1148 (2021)Intel HERACLES: Homomorphic Encryption Revolutionary Accelerator with Correctness for Learning-oriented End-to-End Solutions.. CCSW, page 3. ACM, (2022)Pruning hardware evaluation space via correlation-driven application similarity analysis., , , , , and . Conf. Computing Frontiers, page 4. ACM, (2011)