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An example of SC-FCNN on MNIST. This work is an un-offical implementation of paper: Dynamic Energy-Accuracy Trade-off Using Stochastic Computing in Deep Neural Networks. We use full-SC process, all values are representated as bit-stream. and got result acc = 97.2%.

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Fully-SCNN

An example of SC-FCNN on MNIST. This work is an un-offical implementation of paper: Dynamic Energy-Accuracy Trade-off Using Stochastic Computing in Deep Neural Networks. We use full-SC process, all values are representated as bit-stream. and got result acc = 97.2%.

The first work implement end-to-end PyTorch capable SC process.

Features

  1. Fully-LFSR based SNG, all behavior of hardware are simulated.
  2. An end-to-end process using real bit-stream for calculation.
  3. All Calculation of SC is implementated, using real XNOR, APC, FSM, etc. operation.

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An example of SC-FCNN on MNIST. This work is an un-offical implementation of paper: Dynamic Energy-Accuracy Trade-off Using Stochastic Computing in Deep Neural Networks. We use full-SC process, all values are representated as bit-stream. and got result acc = 97.2%.

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