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SNNAP: Approximate computing on programmable SoCs via neural acceleration.

, , , , , , and . HPCA, page 603-614. IEEE Computer Society, (2015)

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Neural Acceleration for General-Purpose Approximate Programs., , , and . IEEE Micro, 33 (3): 16-27 (2013)FastStereoNet: A Fast Neural Architecture Search for Improving the Inference of Disparity Estimation on Resource-Limited Platforms., , , , , , and . IEEE Trans. Syst. Man Cybern. Syst., 52 (8): 5222-5234 (2022)DCim++: a C++ library for object oriented hardware design and distributed simulation., , , , , and . ISCAS, IEEE, (2006)Neural acceleration for general-purpose approximate programs., , , and . Commun. ACM, 58 (1): 105-115 (2015)Shredder: Learning Noise to Protect Privacy with Partial DNN Inference on the Edge., , , , and . CoRR, (2019)Neural acceleration for GPU throughput processors., , , , and . MICRO, page 482-493. ACM, (2015)Neural Acceleration for General-Purpose Approximate Programs., , , and . MICRO, page 449-460. IEEE Computer Society, (2012)RoboX: An End-to-End Solution to Accelerate Autonomous Control in Robotics., , , and . ISCA, page 479-490. IEEE Computer Society, (2018)How to implement effective prediction and forwarding for fusable dynamic multicore architectures., , , , , , , and . HPCA, page 460-471. IEEE Computer Society, (2013)TABLA: A unified template-based framework for accelerating statistical machine learning., , , , , , and . HPCA, page 14-26. IEEE Computer Society, (2016)