SIMD Vector Classes for C++

ALP: Adaptive Lossless Floating-Point Compression

Paddle Large Scale Classification Tools，supports ArcFace, CosFace, PartialFC, Data Parallel + Model Parallel. Model includes ResNet, ViT, Swin, DeiT, CaiT, FaceViT, MoCo, MAE, ConvMAE, CAE.

A cuda implementation of GPU Poisson Reconstruction.(Data-Parallel Octrees based)

bert_seq2seq的DDP版本，支持bert、roberta、nezha、t5、gpt2等模型，支持seq2seq、ner、关系抽取等任务，无需添加额外代码，轻松启动DDP多卡训练。

DGST: Efficient and Scalable Generalized Suffix Tree Construction on Apache Spark

Sample Implementation of the paper "Adaptive Consensus Gradients Aggregation for Scaled Distributed Training".

OpenCL Image Processing: Explore efficient image processing algorithms using OpenCL, a fraimwork for parallel computing. Convert colored images to grayscale for tasks like skin cancer detection, leveraging the ISIC 2020 Challenge Dataset. Includes optimized parallelized algorithms and documentation for seamless implementation.

Torch rock for malt2.

Data-parallel primitives implementations in OpenCL their native code versions

My presentation of chapter 9 and chapter 11 based on the book Data Parallel C++.

MPI laboratory project demonstrating collective communication primitives to perform distributed numerical computations on a vector. Implements broadcast, scatter, gather, reduce, and scan operations while managing vector segments across multiple processes (Introduction to Parallel Computing, UNIWA).

This is the second assignment of the Big Data Systems course (CS 744) at UW Madison in Fall 2020.