SEOKMIN83

SEOKMIN83's Stars

• prometheus/prometheus

  The Prometheus monitoring system and time series database.

  Language:Go55.1k9.1k

• resource-disaggregation/karma

  Resource Allocation for Dynamic Demands

  Language:C++174

• LeeKyuHyuk/Raspberry-Pi-Bare-Metal

  Raspberry Pi Bare Metal Tutorials

  Language:C3

• namhyung/uftrace

  Function graph tracer for C/C++/Rust/Python

  Language:C3k444

• awslabs/damo

  DAMON user-space tool

  Language:Python15626

• SEOKMIN83/uftrace

  Function graph tracer for C/C++/Rust/Python

  Language:C1

• hyunwoongko/transformer

  Transformer: PyTorch Implementation of "Attention Is All You Need"

  Language:Python2.9k424

• alibaba/clusterdata

  cluster data collected from production clusters in Alibaba for cluster management research

  Language:Jupyter Notebook1.6k405

• junhyeokahn/COMPM050-RL

  Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

  Language:Jupyter Notebook51

• chulminkw/PerfectGuide

  Language:Jupyter Notebook115151

• aayushARM/image-captioning

  Implementation of a Multimodal Neural Network for Image Captioning in Tensorflow.

  Language:Python96

• 504ensicsLabs/LiME

  LiME (formerly DMD) is a Loadable Kernel Module (LKM), which allows the acquisition of volatile memory from Linux and Linux-based devices, such as those powered by Android. The tool supports acquiring memory either to the file system of the device or over the network. LiME is unique in that it is the first tool that allows full memory captures from Android devices. It also minimizes its interaction between user and kernel space processes during acquisition, which allows it to produce memory captures that are more forensically sound than those of other tools designed for Linux memory acquisition.

  Language:C1.7k338

• SNU-YOCO/YOCO

  Cooking AI based on unbiased-teacher v2

  Language:Jupyter Notebook3

• minio/minio

  MinIO is a high-performance, S3 compatible object store, open sourced under GNU AGPLv3 license.

  Language:Go47.1k5.4k

• oslab-ewha/simtbs

  Thread Block Scheduler(TBS) Simulator

  Language:C4

• rickiepark/hg-da

  <혼자 공부하는 데이터 분석 with 파이썬>의 코드 저장소

  Language:Jupyter Notebook4738

• accel-sim/accel-sim-framework

  This is the top-level repository for the Accel-Sim framework.

  Language:Python294113

• stanford-futuredata/gavel

  Code for "Heterogenity-Aware Cluster Scheduling Policies for Deep Learning Workloads", which appeared at OSDI 2020

  Language:Jupyter Notebook12531

• kzhang28/Optimus

  An Efficient Dynamic Resource Scheduler for Deep Learning Clusters

  Language:Python419

• SymbioticLab/Tiresias

  Tiresias is a GPU cluster manager for distributed deep learning training.

  Language:Python14948

• CodeTest-StudyGroup/Code-Test-Study

  코딩 테스트 관련 기출문항을 풀어보고 소스코드 및 설명을 업로드합니다.

  Language:C++1.1k166

• TheCopiens/algorithm-study

  :orange_book: Algorithm study

  Language:C++10215

• CoffeeBeforeArch/cuda_programming

  Code from the "CUDA Crash Course" YouTube series by CoffeeBeforeArch

  Language:Cuda713157

• mml-book/mml-book.github.io

  Companion webpage to the book "Mathematics For Machine Learning"

  Language:Jupyter Notebook13.1k2.4k

• ddangcoonfire/experiment-scheduler

  for easy experiment scheduling. no more boring job

  Language:Python111

• d2l-ai/d2l-en

  Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

  Language:Python23.3k4.3k

• cpm0722/transformer_pytorch

  Transformer(Attention Is All You Need) Implementation in Pytorch

  Language:Python6516

• hunkim/deep_architecture_genealogy

  Deep Learning Architecture Genealogy Project

  Language:Python1.2k196

• hunkim/word-rnn-tensorflow

  Multi-layer Recurrent Neural Networks (LSTM, RNN) for word-level language models in Python using TensorFlow.

  Language:Python1.3k494

• hunkim/PyTorchZeroToAll

  Simple PyTorch Tutorials Zero to ALL!

  Language:Python3.9k1.2k