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Found 4 papers, 0 papers with code
PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel
It is widely acknowledged that large models have the potential to deliver superior performance across a broad range of domains.
Supporting Very Large Models using Automatic Dataflow Graph Partitioning
This paper presents Tofu, a system that partitions very large DNN models across multiple GPU devices to reduce per-GPU memory footprint.
Unifying Data, Model and Hybrid Parallelism in Deep Learning via Tensor Tiling
We present this automatic tiling in a new system, SoyBean, that can act as a backend for Tensorflow, MXNet, and others.
Get More With Less: Near Real-Time Image Clustering on Mobile Phones
In this paper, we show that by combining the computing power distributed over a number of phones, judicious optimization choices, and contextual information it is possible to execute the end-to-end pipeline entirely on the phones at the edge of the network, efficiently.
