Overview
DualPipe proposes a bidirectional pipeline parallelism algorithm to achieve efficient compute-communication overlap in pipeline-parallel training, improving overall throughput and hardware utilization. It has been used in DeepSeek V3/R1 to reduce communication stalls.
Key Features
- Supports bidirectional pipeline parallelism to enhance compute-communication overlap.
- Designed for integration with existing pipeline-parallel frameworks, reducing integration overhead.
- Provides examples and implementation notes to help teams reproduce and optimize in their own training pipelines.
Use Cases
- Large-scale pipeline-parallel training across multiple nodes or GPUs.
- Scenarios where communication stalls hurt throughput and improved scheduling can boost performance.
- Research and engineering teams looking for reference implementations and baselines for parallel strategies.
Technical Details
- Bidirectional pipeline scheduling for better pipeline utilization and communication overlap.
- Focus on scheduling strategies and timing of activation/gradient transfers to reduce idle time.
- Composable with other parallel strategies and adaptable to complex hardware topologies.