Privatar uses horizontal frequency partitioning and distribution-aware minimal perturbation to enable private offloading of VR avatar reconstruction, supporting 2.37x more users with modest overhead.
An Evaluation of Edge TPU Accelerators for Convolutional Neural Networks , publisher =
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Demonstrates single-shot 3D matrix-matrix multiplication in an optical tensor processor that accelerates CNNs and DNNs at 20 aJ per MAC with 96.4% accuracy on image recognition using 292616 parameters.
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Privatar: Scalable Privacy-preserving Multi-user VR via Secure Offloading
Privatar uses horizontal frequency partitioning and distribution-aware minimal perturbation to enable private offloading of VR avatar reconstruction, supporting 2.37x more users with modest overhead.
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Single-Shot Matrix-Matrix Multiplication Optical Tensor Processor for Deep Learning
Demonstrates single-shot 3D matrix-matrix multiplication in an optical tensor processor that accelerates CNNs and DNNs at 20 aJ per MAC with 96.4% accuracy on image recognition using 292616 parameters.