Sep 20, 2020 · We propose VirtualFlow, a system leveraging a novel abstraction called virtual node processing to decouple the model from the hardware. In each ...
ABSTRACT. We propose VirtualFlow, a system leveraging a novel abstraction called virtual node processing to decouple the model from the hardware.
We propose VirtualFlow, a novel system approach leveraging virtual node processing to decouple model execution from the hardware. In each execution step, the ...
The proposed VirtualFlow, a system leveraging a novel abstraction called virtual node processing to decouple the model from the hardware, achieved strong ...
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Sep 20, 2020 · This work introduces EasyScale, an elastic framework that scales distributed training on heterogeneous GPUs while producing deterministic ...
Bibliographic details on VirtualFlow: Decoupling Deep Learning Model Execution from Underlying Hardware.
VirtualFlow: Decoupling Deep Learning Models from the Underlying Hardware. A Or, H Zhang, MN Freedman. Proceedings of Machine Learning and Systems 4, 126-140, ...
VirtualFlow: Decoupling Deep Learning Models from the Underlying Hardware. A Or, H Zhang, MN Freedman. Proceedings of Machine Learning and Systems 4, 126-140, ...
VirtualFlow: Decoupling Deep Learning Models from the Underlying Hardware Andrew Or, Haoyu Zhang, Michael None Freedman; torch.fx: Practical Program Capture ...
VirtualFlow: Decoupling Deep Learning Models from the Underlying Hardware. A Or, H Zhang, MN Freedman. Proceedings of Machine Learning and Systems 4, 126-140, ...