Huangxy-Minel / System-Design-for-Federated-LearningLinks
Paper list of federated learning: About system design
☆13Updated 3 years ago
Alternatives and similar repositories for System-Design-for-Federated-Learning
Users that are interested in System-Design-for-Federated-Learning are comparing it to the libraries listed below
Sorting:
- A Cluster-Wide Model Manager to Accelerate DNN Training via Automated Training Warmup☆35Updated 2 years ago
- Dual-way gradient sparsification approach for async DNN training, based on PyTorch.☆11Updated 2 years ago
- [ACM SoCC'22] Pisces: Efficient Federated Learning via Guided Asynchronous Training☆12Updated 2 months ago
- [ICDCS 2023] Evaluation and Optimization of Gradient Compression for Distributed Deep Learning☆10Updated 2 years ago
- Primo: Practical Learning-Augmented Systems with Interpretable Models☆19Updated last year
- ☆15Updated 3 years ago
- Cupcake: A Compression Scheduler for Scalable Communication-Efficient Distributed Training (MLSys '23)☆9Updated last year
- Federated Learning Framework Benchmark (UniFed)☆49Updated 2 years ago
- ☆14Updated 3 years ago
- Code for "Solving Large-Scale Granular Resource Allocation Problems Efficiently with POP", which appeared at SOSP 2021☆26Updated 3 years ago
- [ACM SIGCOMM 2024] "m3: Accurate Flow-Level Performance Estimation using Machine Learning" by Chenning Li, Arash Nasr-Esfahany, Kevin Zha…☆24Updated 8 months ago
- Create tiny ML systems for on-device learning.☆20Updated 3 years ago
- This repository is the official implementation of 'EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Lea…☆14Updated 2 years ago
- ☆10Updated 4 years ago
- A computation-parallel deep learning architecture.☆13Updated 5 years ago
- A Sparse-tensor Communication Framework for Distributed Deep Learning☆13Updated 3 years ago
- Hi-Speed DNN Training with Espresso: Unleashing the Full Potential of Gradient Compression with Near-Optimal Usage Strategies (EuroSys '2…☆15Updated last year
- This repository contains code for the paper: Bergsma S., Zeyl T., Senderovich A., and Beck J. C., "Generating Complex, Realistic Cloud Wo…☆43Updated 3 years ago
- ☆17Updated last year
- Federated Learning Systems Paper List☆73Updated last year
- Ok-Topk is a scheme for distributed training with sparse gradients. Ok-Topk integrates a novel sparse allreduce algorithm (less than 6k c…☆26Updated 2 years ago
- MobiSys#114☆21Updated last year
- ☆27Updated last year
- Code for reproducing experiments performed for Accoridon☆13Updated 4 years ago
- Surrogate-based Hyperparameter Tuning System☆28Updated 2 years ago
- ☆45Updated 3 years ago
- ☆19Updated 3 years ago
- Artifact for "Shockwave: Fair and Efficient Cluster Scheduling for Dynamic Adaptation in Machine Learning" [NSDI '23]☆44Updated 2 years ago
- Artifact for "Apparate: Rethinking Early Exits to Tame Latency-Throughput Tensions in ML Serving" [SOSP '24]☆25Updated 7 months ago
- Herald: Accelerating Neural Recommendation Training with Embedding Scheduling (NSDI 2024)☆22Updated last year