daitr616's repositories
Topology_Mapping
This is an assignment in the information systems and software course. As simulating large scale network experiments requires lots of physical resources, partitioning can be used. Topology mapping is a partitioning technique that maps the simulated nodes to different physical nodes. In this assignment, we will use spectral clustering to partition a given network topology on the available physical nodes.
awesome-satellite-imagery-datasets
🛰️ List of satellite image training datasets with annotations for computer vision and deep learning
Best-websites-a-programmer-should-visit
:link: Some useful websites for programmers.
biblatex-gb7714-2015
A biblatex implementation of the GB/T7714-2015 bibliography style || GB/T 7714-2015 参考文献著录和标注的biblatex样式包
CarImageClassificationOnHPC
Car Image Classification Using Convolutional Neural Networks (CNN) and using single and multiple GPUs to compare the speedup performance
CoastSat
Global shoreline mapping tool from satellite imagery
CoastSat.islands
Satellite-derived shorelines and 2D planform measurements for islands, extension of the CoastSat toolbox.
CoastSat.slope
Beach-face slope estimation from satellite-derived shorelines, extension of the CoastSat toolbox.
deeplearning-models
A collection of various deep learning architectures, models, and tips
DNN_NeuroSim_V2.0
Benchmark framework of compute-in-memory based accelerators for deep neural network (on-chip training chip focused)
fairscale
PyTorch extensions for high performance and large scale training.
flatland-reinforcement-learning
Multi-Agent Reinforcement Learning for optimal train schedules
gpubootcamp
This repository consists for gpu bootcamp material for HPC and AI
Graphite
A parallel, distributed simulator for multicores.
gym
A toolkit for developing and comparing reinforcement learning algorithms.
hpc-parallel-novice
Introductory material on parallelization using python with a focus on HPC platforms
imgclsmob
Sandbox for training deep learning networks
machine-learning
Collection of Jupyter notebooks with examples of machine learning - supervised, unsupervised and reinforcement learning models.
mas_basics
the basics of multi-agent systems in python
mit-deep-learning-book-pdf
MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville
mobile-vision
Mobile vision models and code
models
Models and examples built with TensorFlow
oneDNN
oneAPI Deep Neural Network Library (oneDNN)
OpenCoarrays
A parallel application binary interface for Fortran 2018 compilers.
optical-rl-gym
Set of reinforcement learning environments for optical networks
optimizers
examples of lp optimization in python
pipedream
focus
protobuf
Protocol Buffers - Google's data interchange format
tutorials
PyTorch tutorials.
vision
Datasets, Transforms and Models specific to Computer Vision