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Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Network., , , , , , и . ISCA, стр. 764-775. IEEE Computer Society, (2018)Accelerating String-Key Learned Index Structures via Memoization-based Incremental Training., , , , , и . CoRR, (2024)DaCapo: Accelerating Continuous Learning in Autonomous Systems for Video Analytics., , , , , , , , и . CoRR, (2024)FlexJava: language support for safe and modular approximate programming., , , , и . ESEC/SIGSOFT FSE, стр. 745-757. ACM, (2015)Rollback-free value prediction with approximate loads., , , , , , , и . PACT, стр. 493-494. ACM, (2014)Towards Statistical Guarantees in Controlling Quality Tradeoffs for Approximate Acceleration., , , , и . ISCA, стр. 66-77. IEEE Computer Society, (2016)Mixed-Signal Charge-Domain Acceleration of Deep Neural Networks through Interleaved Bit-Partitioned Arithmetic., , , , , , , и . PACT, стр. 399-411. ACM, (2020)TNPU: Supporting Trusted Execution with Tree-less Integrity Protection for Neural Processing Unit., , , , и . HPCA, стр. 229-243. IEEE, (2022)Supporting Dynamic Translation Granularity for Hybrid Memory Systems., , , , , и . ICCD, стр. 25-32. IEEE, (2022)TABLA: A unified template-based framework for accelerating statistical machine learning., , , , , , и . HPCA, стр. 14-26. IEEE Computer Society, (2016)