Dong Dai's starred repositories
typst-examples-book
Book of educational examples for Typst
modern-nju-thesis
南京大学学位论文 Typst 模板 modern-nju-thesis
Gaussian-Process-Regression-Tutorial
An Intuitive Tutorial to Gaussian Processes Regression
ycsb-storedsbench
A Performance Study of Optane Persistent Memory: From Indexing Data Structures’ Perspective [MSST'20]
deep-batch-scheduler
RLScheduler: An AutomatedHPC Batch Job Scheduler Using Reinforcement Learning [SC'20]
LustrePerfMon
Lustre Monitoring System based on Collectd, Grafana and Influxdb
Lustre-Simulator
The Lustre simulator was developed as a simulation platform to research scalability, analyze I/O behaviors and design various algorithms at large scale. It simulates disks, the Linux I/O elevator, a file system with mballoc block allocation, a packet-level network, and three Lustre subsystems: client, MDS and OSS. The Lustre simulator can simulate concurrent operations by 100,000 clients.
PyTorch-BigGraph
Generate embeddings from large-scale graph-structured data.
deeplearning4j
Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learn...
org-html-themes
Transform your Org mode files into stunning HTML documents in minutes with our Org mode HTML theme. Elevate your productivity and impress your readers! #orgmode #html #theme #productivity #design
reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
reinforcement-learning-an-introduction
Python Implementation of Reinforcement Learning: An Introduction
darwin-xnu
Legacy mirror of Darwin Kernel. Replaced by https://github.com/apple-oss-distributions/xnu
TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
paper-end2end-dl
📝 "End-to-end Deep Learning of Optimization Heuristics" (🥇 PACT'17 Best Paper)