fanshiqing/gloo — explained in plain English
Analysis updated 2026-07-18 · repo last pushed 2019-01-25
Synchronize gradients across 100 GPUs spread over multiple machines during large model training.
Use allreduce to combine results from all machines and send the combined result back to everyone.
Move data directly GPU-to-GPU across machines using GPUDirect for faster training.
Embed Gloo's collective operations into a custom distributed training system.
| fanshiqing/gloo | achanana/mavsdk | alange/llama.cpp | |
|---|---|---|---|
| Stars | — | — | 0 |
| Language | C++ | C++ | C++ |
| Last pushed | 2019-01-25 | 2024-05-20 | — |
| Maintenance | Dormant | Dormant | — |
| Setup difficulty | hard | moderate | moderate |
| Complexity | 5/5 | 4/5 | 4/5 |
| Audience | researcher | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires a multi-machine cluster setup and coordination infrastructure like Redis or MPI, GPUDirect needs compatible NVIDIA hardware.
A communications library that lets many machines share data efficiently during distributed machine learning training, handling the syncing so engineers don't build it themselves.
Mainly C++. The stack also includes C++, TCP/IP, InfiniBand.
Dormant — no commits in 2+ years (last push 2019-01-25).
Setup difficulty is rated hard, with roughly 1day+ to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
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