pengmiao-usc

pengmiao-usc's Stars

• youngyangyang04/leetcode-master

  《代码随想录》LeetCode 刷题攻略：200道经典题目刷题顺序，共60w字的详细图解，视频难点剖析，50余张思维导图，支持C++，Java，Python，Go，JavaScript等多语言版本，从此算法学习不再迷茫！🔥🔥 来看看，你会发现相见恨晚！🚀

  Language:Shell52.6k38324411.6k

• microsoft/Swin-Transformer

  This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

  Language:Python14.1k1273152.1k

• locuslab/TCN

  Sequence modeling benchmarks and temporal convolutional networks

  Language:Python4.2k9374883

• KikiLetGo/CyberController

  CyberController

  Language:Java1.3k137251

• ZeweiChu/PyTorch-Course

  JULYEDU PyTorch Course

  Language:Jupyter Notebook1.1k266516

• MorvanZhou/NLP-Tutorials

  Simple implementations of NLP models. Tutorials are written in Chinese on my website https://mofanpy.com

  Language:Python9171716313

• Eric-mingjie/network-slimming

  Network Slimming (Pytorch) (ICCV 2017)

  Language:Python9111493213

• foolwood/pytorch-slimming

  Learning Efficient Convolutional Networks through Network Slimming, In ICCV 2017.

  Language:Python568111695

• joennlae/halutmatmul

  Hashed Lookup Table based Matrix Multiplication (halutmatmul) - Stella Nera accelerator

  Language:Python20710412

• JianxGao/C-machine-learning

  C语言手撕机器学习/深度学习算法

  Language:C1191437

• CMU-SAFARI/Pythia

  A customizable hardware prefetching framework using online reinforcement learning as described in the MICRO 2021 paper by Bera et al. (https://arxiv.org/pdf/2109.12021.pdf).

  Language:C++11891037

• dna1980drys/mnistGNN

  MNIST classification by using GCN

  472011

• Anton-Cherepkov/gnn-mnist-classification

  Image classification using Graph Neural Networks (GNNs) with MNIST dataset

  Language:Python36228

• stevenpelley/atomic-memory-trace

  PIN-tool to produce multi-threaded atomic memory traces

  Language:C++343010

• jichengyuan/Vision_GNN

  Language:Jupyter Notebook28143

• tedzhouhk/GCNP

  Language:Python16207

• kartiklakhotia/pcpm

  partition-centric GAS based pagerank computation

  Language:C++9313

• pengmiao-usc/TransFetch

  TransFetch

  Language:C++7128

• souravpati/GPOP

  GPOP: A scalable cache- and memory-efficient framework for Graph Processing Over Partitions

  Language:C++7314

• ab7289-tandon-nyu/GraphVision

  Evaluating the feasibility of GNN algorithms with Image Classification.

  Language:Jupyter Notebook5102

• mao1207/neural-network-computation-acceleration

  Reproduce the fast matrix multiplication method based on Multiplying Matrices Without Multiplying and Bolt: Accelerated Data Mining with Fast Vector Compression , while doing the speedup of the underlying operator.

  Language:Python4201

• MemMAP/C-MemMAP

  C-MemMAP: Clustering-driven Compact, Adaptable, and Generalizable Meta-LSTM Models for Memory Access Prediction

  Language:Python4103

• pgroupATusc/C-MemMAP

  C-MemMAP: Clustering-driven Compact, Adaptable, and Generalizable Meta-LSTM Models for Memory Access Prediction

  Language:Python3000

• tedzhouhk/SeDyT

  Language:Python3202

• neeleshg23/TabConv

  Low-Computation CNN Inference via Table Lookups

  Language:Python21

• pgroupATusc/ReSemble

  ReSemble: Reinforced Ensemble Framework for Data Prefetching

  Language:Python2000

• compor/prodigy_compiler_support_public

  1302

• flyniu666/PowerGraph-build

  Language:CMake12

• neeleshg23/PaCKD

  PaCKD: Pattern-Clustered Knowledge Distillation for Compressing Memory Access Prediction Models

  Language:Python1101

• pgroupATusc/GPOP

  GPOP: A scalable cache- and memory-efficient framework for Graph Processing Over Partitions

  Language:C++1001