Abstract: We have conducted 175 billion parameters, 1024 GPUs large language model training with up to $99.41 \%$ (Pipeline parallel, PP) and $98.95 \%$ (Data parallel, DP) training efficiency in two ...
Abstract: The rise of edge intelligence is driving distributed machine learning toward a new paradigm of edge-collaborative computing. To overcome the severe communication bottleneck in this paradigm, ...
local-global-graph-transformer/ ├── config/ │ ├── defaults.yaml # Edit simulation/training parameters here │ ├── paths.py # Automatic path management (linear/nonlinear) │ └── constants.py # Physical ...
This demo demonstrates a distributed locking mechanism using Apache ZooKeeper to coordinate access between multiple API replicas trying to write to a shared text file. In distributed systems, multiple ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results