walkershaw

cccl

CUDA C++ Core Libraries

diagrammer

Provides dot visualizations of chisel/firrtl circuits

bert

TensorFlow code and pre-trained models for BERT

mesh

Mesh TensorFlow: Model Parallelism Made Easier

osdt-weekly

开源开发工具周刊

Ax

Adaptive Experimentation Platform

BayesianOptimization

A Python implementation of global optimization with gaussian processes.

DAC-2020-Tutorial

Material for OpenROAD Tutorial at DAC 2020

overleaf

A web-based collaborative LaTeX editor

kendryte-standalone-demo

Demo of kendryte k210 standalone SDK

GMatch4py

A graph matching library for Python

darknet

Convolutional Neural Networks

RapidWright

Build Customized FPGA Implementations for Vivado

TAPAS

CHaiDNN

HLS based Deep Neural Network Accelerator Library for Xilinx Ultrascale+ MPSoCs

caffe

Ristretto: Caffe-based approximation of convolutional neural networks.

gemx

Matrix Operation Library for FPGA https://xilinx.github.io/gemx/

QNN-MO-PYNQ

BNN-PYNQ

Quantized Neural Networks (QNNs) on PYNQ

ml-suite

Getting Started with Xilinx ML Suite

hipacc-fpga

Fork of Hipacc generating code for Vivado HLS and Altera OpenCL

weld

High-performance runtime for data analytics applications

Benchmark_SpMV_using_CSR5

CSR5-based SpMV on CPUs, GPUs and Xeon Phi

Caffe-HRT

Heterogeneous Run Time version of Caffe. Added heterogeneous capabilities to the Caffe, uses heterogeneous computing infrastructure framework to speed up Deep Learning on Arm-based heterogeneous embedded platform. It also retains all the features of the original Caffe architecture which users deploy their applications seamlessly.

xlearn

High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

Sparso

Julia package for accelerating sparse matrix applications.

DeepBench

Benchmarking Deep Learning operations on different hardware

taco

The Tensor Algebra Compiler (taco) computes sparse tensor expressions on CPUs and GPUs

SparseConvNet-archived

Spatially-sparse convolutional networks. Allows processing of sparse 2, 3 and 4 dimensional data.Build CNNs on the square/cubic/hypercubic or triangular/tetrahedral/hyper-tetrahedral lattices.

SOI_FFT

Segment-of-interest low-communication FFT algorithm