Comments (3)
you can train it with as many as GPUs in a single machine. If you use --gpu 0 --use_data_parallel
then Pytorch will use all GPUs in your machine.
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Got it. Thanks, Dr. Tian!
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@yuandong-tian
In this announcement https://facebook.ai/developers/tools/elf
It is said that ELF OpenGo was trained by 2000 GPUs.
My question is 2000 GPUs were used for training only? Or also used for selfplaying and evaluating?
And if 2000 GPUs were on a single machine or on multiple machines? If multi machines then we can setup training on multi servers using this source code?
Thank you!
from elf.
Related Issues (20)
- Can't compile in ubunu 18.10, gcc 8.2, cmake 3.12.1 HOT 1
- Is a 40b net run considered ? HOT 1
- will your team accept the match invitation HOT 1
- can elf go run with pytorch v1.1
- feature request: Jetson Nano build & instructions?
- releases: pretrained-go-9x9 HOT 1
- [question] Typical value of resign threshold during training HOT 1
- GoGoD commentary SGFs with an illegal move
- RuntimeError:Device index must not be negetive HOT 2
- missing ./analysis.sh
- Startup script example to run trainer on single GPU machine (small board)? HOT 2
- WARNING! no servers has the label: game_start HOT 2
- NFS for Clients and Server
- How to use ELF in Sabaki or gogui?
- [elf::comm::Client-4] [warning] WARNING! no servers has the label: game_start
- How to parse SGF files analyzed by ELF GO
- Confusion about the updateEdgeStats()
- [warning] WARNING! no servers has the label: game_start
- Why using cpp?
- Running a Go bot,enter Pdb environment
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