llljun Goto Github PK

addernet

Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"

big-ann-benchmarks

Framework for evaluating ANNS algorithms on billion scale datasets.

cacti

An integrated cache and memory access time, cycle time, area, leakage, and dynamic power model

cuda_freshman

cuhnsw

CUDA implementation of Hierarchical Navigable Small World Graph algorithm

data-science-notes

数据科学的笔记以及资料搜集

dcl

Destruction and Construction Learning for Fine-grained Image Recognition

dgsparse-library

diskann

Graph based indices for approximate nearest neighbor search

diskann_nics

dpu_demo

Examples of DPU programs using the UPMEM DPU SDK

efanna

fast library for ANN search and KNN graph construction

faiss

A library for efficient similarity search and clustering of dense vectors.

gcn

Implementation of Graph Convolutional Networks in TensorFlow

github-slideshow

A robot powered training repository :robot:

google-research

Google Research

hello-world

hnsw_nics

hnswlib

Header-only C++/python library for fast approximate nearest neighbors

learn-to-cluster

Learning to Cluster Faces (CVPR 2019, CVPR 2020)

lstm-neural-network-for-time-series-prediction

LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

meituan-food-recognition

Codes for Fine-grained Food Recognition

metis

METIS - Serial Graph Partitioning and Fill-reducing Matrix Ordering

mqsim

MQSim is a fast and accurate simulator modeling the performance of modern multi-queue (MQ) SSDs as well as traditional SATA based SSDs. MQSim faithfully models new high-bandwidth protocol implementations, steady-state SSD conditions, and the full end-to-end latency of requests in modern SSDs. It is described in detail in the FAST 2018 paper by Arash Tavakkol et al., "MQSim: A Framework for Enabling Realistic Studies of Modern Multi-Queue SSD Devices" (https://people.inf.ethz.ch/omutlu/pub/MQSim-SSD-simulation-framework_fast18.pdf)

nns_benchmark

Benchmark of Nearest Neighbor Search on High Dimensional Data

nsg

Navigating Spreading-out Graph For Approximate Nearest Neighbor Search

pim-embedding-lookup

predictive-maintenance-using-lstm

Example of Multiple Multivariate Time Series Prediction with LSTM Recurrent Neural Networks in Python with Keras.

pytorch-handbook

pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行

rtl_library_of_basic_hardware_units

Here are some mplementations of some basic hardware units in RTL language (verilog for now), which can be used for area/power evaluation and support the hardware design tradeoff.