Alternatives and similar repositories for Overlap_Local_SGD

Users that are interested in Overlap_Local_SGD are comparing it to the libraries listed below

• epfml / LocalSGD-Code
  ☆46Updated 5 years ago
• epfml / sparsifiedSGD
  Sparsified SGD with Memory: https://arxiv.org/abs/1809.07599
  ☆59Updated 6 years ago
• jiaweizzhao / signSGD-with-Majority-Vote
  ☆77Updated 6 years ago
• epfml / powersgd
  Practical low-rank gradient compression for distributed optimization: https://arxiv.org/abs/1905.13727
  ☆148Updated 11 months ago
• jxbz / signSGD
  Code for the signSGD paper
  ☆91Updated 4 years ago
• epfml / ChocoSGD
  Decentralized SGD and Consensus with Communication Compression: https://arxiv.org/abs/1907.09356
  ☆72Updated 5 years ago
• lusinlu / deep-gradient-compression
  Partial implementation of paper "DEEP GRADIENT COMPRESSION: REDUCING THE COMMUNICATION BANDWIDTH FOR DISTRIBUTED TRAINING"
  ☆31Updated 4 years ago
• xinyandai / gradient-quantization
  vector quantization for stochastic gradient descent.
  ☆35Updated 5 years ago
• facebookresearch / stochastic_gradient_push
  Stochastic Gradient Push for Distributed Deep Learning
  ☆169Updated 2 years ago
• chaoyanghe / FedNAS
  FedNAS: Federated Deep Learning via Neural Architecture Search
  ☆54Updated 4 years ago
• dhroth / sketchedsgd
  Sketched SGD
  ☆28Updated 5 years ago
• epfml / error-feedback-SGD
  SGD with compressed gradients and error-feedback: https://arxiv.org/abs/1901.09847
  ☆31Updated last year
• Tabrizian / learning-to-quantize
  Code for "Adaptive Gradient Quantization for Data-Parallel SGD", published in NeurIPS 2020.
  ☆30Updated 4 years ago
• synxlin / deep-gradient-compression
  [ICLR 2018] Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training
  ☆224Updated last year
• nikitaivkin / csh
  Simple Hierarchical Count Sketch in Python
  ☆21Updated 4 years ago
• hwang595 / ATOMO
  Atomo: Communication-efficient Learning via Atomic Sparsification
  ☆27Updated 6 years ago
• rdspring1 / Count-Sketch-Optimizers
  A compressed adaptive optimizer for training large-scale deep learning models using PyTorch
  ☆27Updated 5 years ago
• alecwangcq / GraSP
  Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH
  ☆106Updated 5 years ago
• hclhkbu / GaussianK-SGD
  Understanding Top-k Sparsification in Distributed Deep Learning
  ☆24Updated 5 years ago
• alshedivat / fedpa
  Federated posterior averaging implemented in JAX
  ☆51Updated 2 years ago
• hwang595 / PyTorch-parameter-server
  Implementation of Parameter Server using PyTorch communication lib
  ☆42Updated 6 years ago
• sands-lab / grace
  GRACE - GRAdient ComprEssion for distributed deep learning
  ☆140Updated last year
• IST-DASLab / WoodFisher
  Code accompanying the NeurIPS 2020 paper: WoodFisher (Singh & Alistarh, 2020)
  ☆53Updated 4 years ago
• congxie1108 / iclr2020_zeno_async
  Source code of ICLR2020 submisstion: Zeno++: Robust Fully Asynchronous SGD
  ☆13Updated 5 years ago
• scottjiao / Gradient-Compression-Methods
  ☆33Updated 5 years ago
• slowbull / DDG
  A PyTorch implementation of the paper "Decoupled Parallel Backpropagation with Convergence Guarantee"
  ☆29Updated 7 years ago
• lolemacs / continuous-sparsification
  Implementation of Continuous Sparsification, a method for pruning and ticket search in deep networks
  ☆33Updated 3 years ago
• MingSun-Tse / Awesome-Pruning-at-Initialization
  [IJCAI'22 Survey] Recent Advances on Neural Network Pruning at Initialization.
  ☆59Updated 2 years ago
• RAIVNLab / STR
  Soft Threshold Weight Reparameterization for Learnable Sparsity
  ☆91Updated 2 years ago
• namhoonlee / snip-public
  SNIP: SINGLE-SHOT NETWORK PRUNING BASED ON CONNECTION SENSITIVITY
  ☆115Updated 6 years ago