Practical Solutions for Distributed Training with Heterogeneous GPUs
Challenges in Model Training
Training large models requires significant memory and computing power, which can be addressed by effectively utilizing heterogeneous GPU resources.
Introducing Poplar
Poplar is a groundbreaking distributed training system that extends ZeRO to include heterogeneous GPUs, ensuring maximum global throughput and load balancing.
Performance Validation
Poplar outperformed other approaches in real-world heterogeneous GPU clusters, accelerating training speed and ensuring efficient cluster utilization.
Future Research
The team plans to investigate using ZeRO in heterogeneous clusters with network constraints and explore uneven distribution of model parameters among diverse devices.
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Benefits of Poplar
Stay competitive and redefine your way of work with Poplar, a distributed training system that extends ZeRO with heterogeneous-aware capabilities.
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