lzhangbv / dear_pytorch
[ICDCS 2023] DeAR: Accelerating Distributed Deep Learning with Fine-Grained All-Reduce Pipelining
☆12Updated last year
Alternatives and similar repositories for dear_pytorch:
Users that are interested in dear_pytorch are comparing it to the libraries listed below
- A Cluster-Wide Model Manager to Accelerate DNN Training via Automated Training Warmup☆34Updated 2 years ago
- ddl-benchmarks: Benchmarks for Distributed Deep Learning☆37Updated 4 years ago
- (NeurIPS 2022) Automatically finding good model-parallel strategies, especially for complex models and clusters.☆37Updated 2 years ago
- Official resporitory for "IPDPS' 24 QSync: Quantization-Minimized Synchronous Distributed Training Across Hybrid Devices".☆19Updated 10 months ago
- ☆24Updated last year
- PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models. ICML 2021☆55Updated 3 years ago
- A Deep Learning Cluster Scheduler☆37Updated 4 years ago
- ☆16Updated 2 years ago
- Machine Learning System☆14Updated 4 years ago
- ☆48Updated 7 months ago
- A resilient distributed training framework☆88Updated 9 months ago
- An Attention Superoptimizer☆20Updated 8 months ago
- [IJCAI2023] An automated parallel training system that combines the advantages from both data and model parallelism. If you have any inte…☆51Updated last year
- ☆13Updated 2 years ago
- Ok-Topk is a scheme for distributed training with sparse gradients. Ok-Topk integrates a novel sparse allreduce algorithm (less than 6k c…☆23Updated 2 years ago
- Official repository for the paper DynaPipe: Optimizing Multi-task Training through Dynamic Pipelines☆17Updated last year
- Tacker: Tensor-CUDA Core Kernel Fusion for Improving the GPU Utilization while Ensuring QoS☆18Updated 3 years ago
- ☆70Updated 3 years ago
- DISB is a new DNN inference serving benchmark with diverse workloads and models, as well as real-world traces.☆53Updated 4 months ago
- ☆43Updated 3 years ago
- Cupcake: A Compression Scheduler for Scalable Communication-Efficient Distributed Training (MLSys '23)☆9Updated last year
- ☆18Updated 2 years ago
- ☆69Updated last year
- ☆35Updated 4 years ago
- Cavs: An Efficient Runtime System for Dynamic Neural Networks☆13Updated 4 years ago
- SOTA Learning-augmented Systems☆34Updated 2 years ago
- An external memory allocator example for PyTorch.☆14Updated 3 years ago
- FTPipe and related pipeline model parallelism research.☆41Updated last year
- BytePS examples (Vision, NLP, GAN, etc)☆19Updated 2 years ago
- Artifacts for our ASPLOS'23 paper ElasticFlow☆53Updated 8 months ago