hwang595 / ATOMOLinks
Atomo: Communication-efficient Learning via Atomic Sparsification
☆27Updated 7 years ago
Alternatives and similar repositories for ATOMO
Users that are interested in ATOMO are comparing it to the libraries listed below
Sorting:
- Sparsified SGD with Memory: https://arxiv.org/abs/1809.07599☆58Updated 7 years ago
- Code for the signSGD paper☆90Updated 4 years ago
- Stochastic Gradient Push for Distributed Deep Learning☆170Updated 2 years ago
- gTop-k S-SGD: A Communication-Efficient Distributed Synchronous SGD Algorithm for Deep Learning☆36Updated 6 years ago
- QSGD-TF☆21Updated 6 years ago
- [ICLR 2018] Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training☆225Updated last year
- Algorithm: Decentralized Parallel Stochastic Gradient Descent☆47Updated 7 years ago
- Sketched SGD☆28Updated 5 years ago
- Partial implementation of paper "DEEP GRADIENT COMPRESSION: REDUCING THE COMMUNICATION BANDWIDTH FOR DISTRIBUTED TRAINING"☆31Updated 5 years ago
- vector quantization for stochastic gradient descent.☆35Updated 5 years ago
- GRACE - GRAdient ComprEssion for distributed deep learning☆139Updated last year
- SGD with compressed gradients and error-feedback: https://arxiv.org/abs/1901.09847☆31Updated last year
- Understanding Top-k Sparsification in Distributed Deep Learning☆24Updated 6 years ago
- Decentralized SGD and Consensus with Communication Compression: https://arxiv.org/abs/1907.09356☆74Updated 5 years ago
- ☆77Updated 6 years ago
- Practical low-rank gradient compression for distributed optimization: https://arxiv.org/abs/1905.13727☆149Updated last year
- Ternary Gradients to Reduce Communication in Distributed Deep Learning (TensorFlow)☆182Updated 7 years ago
- Implementation of (overlap) local SGD in Pytorch☆34Updated 5 years ago
- FedNAS: Federated Deep Learning via Neural Architecture Search☆54Updated 4 years ago
- ☆46Updated 5 years ago
- It is implementation of Research paper "DEEP GRADIENT COMPRESSION: REDUCING THE COMMUNICATION BANDWIDTH FOR DISTRIBUTED TRAINING". Deep g…☆18Updated 6 years ago
- PyTorch for benchmarking communication-efficient distributed SGD optimization algorithms☆78Updated 4 years ago
- Federated Multi-Task Learning☆131Updated 7 years ago
- Implementation of Parameter Server using PyTorch communication lib☆42Updated 6 years ago
- Dual-way gradient sparsification approach for async DNN training, based on PyTorch.☆11Updated 3 years ago
- Simple Hierarchical Count Sketch in Python☆21Updated 4 years ago
- ☆30Updated 5 years ago
- Salvaging Federated Learning by Local Adaptation☆56Updated last year
- Bayesian Nonparametric Federated Learning of Neural Networks☆146Updated 6 years ago
- ☆33Updated 6 years ago