Stars
A library to create and manage configuration files, especially for machine learning projects.
An abstraction library for interfacing EDA tools
[FPGA 2020] Open sourced implementation for the ACM/SIGDA FPGA '20 paper titled "GraphACT: Accelerating GCN Training on CPU-FPGA Heterogeneous Platforms"
Repository for benchmarking graph neural networks
A compiler from AI model to RTL (Verilog) accelerator in FPGA hardware with auto design space exploration.
Must-read papers on graph neural networks (GNN)
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
Random instruction generator for RISC-V processor verification
SystemC/C++ library of commonly-used hardware functions and components for HLS.
Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)
Transmit data using ultrasonic audio. Perfect for offline/network-free data transfer, automatic content recognition (ACR), and broadcast.
Graph Neural Network Library for PyTorch
Explore the energy-efficient dataflow scheduling for neural networks.
Implementation of End-to-End Memory Network in PyTorch
A TensorFlow implementation of the Differentiable Neural Computer.
A TensorFlow implementation of DeepMind's Differential Neural Computers (DNC)
Reference implementations of neural networks with differentiable memory mechanisms (NTM, Stack RNN, etc.)
Neural Turing Machine (NTM) & Differentiable Neural Computer (DNC) with pytorch & visdom
Pytorch implementation of DeepMind's differentiable neural computer paper.
This is originally a collection of papers on neural network accelerators. Now it's more like my selection of research on deep learning and computer architecture.
Converter of Synthesizable SystemVerilog to Verilog code
The most cited deep learning papers
A 32-bit Microcontroller featuring a RISC-V core
Customization of waf to create a test framework and build tool for RTL