IST-DASLab / M-FACLinks
Efficient reference implementations of the static & dynamic M-FAC algorithms (for pruning and optimization)
☆17Updated 3 years ago
Alternatives and similar repositories for M-FAC
Users that are interested in M-FAC are comparing it to the libraries listed below
Sorting:
- Practical low-rank gradient compression for distributed optimization: https://arxiv.org/abs/1905.13727☆149Updated last year
- ☆222Updated 2 years ago
- ☆46Updated 5 years ago
- Accuracy 77%. Large batch deep learning optimizer LARS for ImageNet with PyTorch and ResNet, using Horovod for distribution. Optional acc…☆38Updated 4 years ago
- Code accompanying the NeurIPS 2020 paper: WoodFisher (Singh & Alistarh, 2020)☆53Updated 4 years ago
- ☆43Updated 3 years ago
- Block Sparse movement pruning☆81Updated 5 years ago
- Implementation of Continuous Sparsification, a method for pruning and ticket search in deep networks☆33Updated 3 years ago
- [NeurIPS 2022] A Fast Post-Training Pruning Framework for Transformers☆192Updated 2 years ago
- Implementation of (overlap) local SGD in Pytorch☆34Updated 5 years ago
- Sketched SGD☆28Updated 5 years ago
- Parameter Efficient Transfer Learning with Diff Pruning☆74Updated 4 years ago
- Pytorch implementation of the paper "SNIP: Single-shot Network Pruning based on Connection Sensitivity" by Lee et al.☆110Updated 6 years ago
- Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH☆105Updated 5 years ago
- A curated list of early exiting (LLM, CV, NLP, etc)☆69Updated last year
- PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models. ICML 2021☆55Updated 4 years ago
- Soft Threshold Weight Reparameterization for Learnable Sparsity☆90Updated 2 years ago
- ☆41Updated 4 years ago
- Code for the NeurIPS 2022 paper "Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning".☆129Updated 2 years ago
- Block-sparse primitives for PyTorch☆160Updated 4 years ago
- ☆194Updated last week
- [ICLR 2021] HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark☆114Updated 2 years ago
- GRACE - GRAdient ComprEssion for distributed deep learning☆139Updated last year
- ☆228Updated last year
- Python package for rematerialization-aware gradient checkpointing☆27Updated 2 years ago
- Generic Neural Architecture Search via Regression (NeurIPS'21 Spotlight)☆36Updated 3 years ago
- [ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, De…☆45Updated 2 years ago
- Lightweight torch implementation of rigl, a sparse-to-sparse optimizer.☆60Updated 4 years ago
- Efficient LLM Inference Acceleration using Prompting☆51Updated last year
- ☆94Updated 3 years ago