stochastic computing with dianet

Seminar report and presentation slides on topic Stochastic Computational Deep Belief Network

Supplementary material for a manuscript in IEEE TCAD

Solving stochastic problems involving Markov Chains

This is a transaction-level, event-driven python-based simulator for evaluation of stochastic computing based optical neural network accelerators for various quantized Convolutional Neural Network models. This can generate metrics of an accelerator like latency, area, energy consumption and power

A domain-specific language for bitstream computing

Stochastic computing audio synthesizer

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%.

Fully Hardware-Based Stochastic Neural Network

Stochastic Computing for Deep Neural Networks

This is a general-purpose simulator for unary computing based on PyTorch, with the paper accepted to ISCA 2020 and awarded IEEE Micro Top Pick for 2020.

A systolic array simulator for multi-cycle MACs and varying-byte words, with the paper accepted to HPCA 2022.

Nerual Network of Stochastic Computing for MNIST Recognition