msr-fiddle / pipedreamLinks
☆392Updated 3 years ago
Alternatives and similar repositories for pipedream
Users that are interested in pipedream are comparing it to the libraries listed below
Sorting:
- An Efficient Pipelined Data Parallel Approach for Training Large Model☆76Updated 4 years ago
- Microsoft Collective Communication Library☆371Updated 2 years ago
- Resource-adaptive cluster scheduler for deep learning training.☆448Updated 2 years ago
- Fine-grained GPU sharing primitives☆146Updated 3 months ago
- Fast and Adaptive Distributed Machine Learning for TensorFlow, PyTorch and MindSpore.☆297Updated last year
- A baseline repository of Auto-Parallelism in Training Neural Networks☆147Updated 3 years ago
- PipeSwitch: Fast Pipelined Context Switching for Deep Learning Applications☆126Updated 3 years ago
- A GPipe implementation in PyTorch☆858Updated last year
- Synthesizer for optimal collective communication algorithms☆119Updated last year
- A flexible and efficient deep neural network (DNN) compiler that generates high-performance executable from a DNN model description.☆995Updated last year
- The Tensor Algebra SuperOptimizer for Deep Learning☆730Updated 2 years ago
- ☆145Updated 9 months ago
- A tensor-aware point-to-point communication primitive for machine learning☆275Updated this week
- Lightweight and Parallel Deep Learning Framework☆264Updated 2 years ago
- [MLSys 2021] IOS: Inter-Operator Scheduler for CNN Acceleration☆200Updated 3 years ago
- Model-less Inference Serving☆92Updated 2 years ago
- Simple Distributed Deep Learning on TensorFlow☆134Updated 4 months ago
- A high-performance distributed deep learning system targeting large-scale and automated distributed training.☆326Updated 3 months ago
- ☆80Updated 5 months ago
- GRACE - GRAdient ComprEssion for distributed deep learning☆140Updated last year
- Code for "Heterogenity-Aware Cluster Scheduling Policies for Deep Learning Workloads", which appeared at OSDI 2020☆131Updated last year
- NCCL Fast Socket is a transport layer plugin to improve NCCL collective communication performance on Google Cloud.☆122Updated last year
- 🔮 Execution time predictions for deep neural network training iterations across different GPUs.☆62Updated 2 years ago
- AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving (OSDI 23)☆89Updated 2 years ago
- GPU-scheduler-for-deep-learning☆210Updated 5 years ago
- FTPipe and related pipeline model parallelism research.☆43Updated 2 years ago
- AI and Memory Wall☆220Updated last year
- ☆156Updated last year
- Easy Parallel Library (EPL) is a general and efficient deep learning framework for distributed model training.☆270Updated 2 years ago
- ☆83Updated 4 months ago