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4/10/19

QNAP NAS recommended software configuration for AI development

QNAP NAS for AI - TS2888X


AI is a hot topic, and now we are trying to create AI application directly on the storage server (NAS). QNAP NAS bundle with QNAP OS - QTS, to start AI application development on QNAP NAS, the first step is GPU:

1. How to setup GPU on QNAP NAS (QTS)
2. QNAP Nvidia GPU Driver release note 

QNAP QTS 4.3.X / NVIDIA GPU Driver 1.2.x / 384
QNAP QTS 4.4.X / NVIDIA GPU Driver 2.0.x / 410


QTS 4.3.x : NVIDIA GPU Driver 1.2.x

[Libraries update]
- Nvidia Driver updated to 384.111
- Cuda updated to 9.0 ,
- ffmpeg updated to 3.4
- Added 10bit transcode.

Suggest AI framework:


Docker nameTag
tensorflow/tensorflow1.11.0-gpu
pytorch/pytorch0.4.1-cuda9-cudnn7-devel
bvlc/caffegpu
mxnet/python1.3.1_gpu_cu90_mkl_py3
microsoft/cntk2.6-gpu-python3.5-cuda9.0-cudnn7.0
chainer/chainerv5.0.0b4-python3
QTS 4.4.x : NVIDIA GPU Driver 2.0.x

[Libraries update]
- Nvidia Driver updated to 410.78
- Cuda updated to 10.0 ,
- ffmpeg updated to 34.1



Suggest AI framework:


Docker nameTag
tensorflow/tensorflow1.11.0-gpu
pytorch/pytorch1.0.1-cuda10.0-cudnn7-devel
bvlc/caffegpu
mxnet/python1.3.1_gpu_cu92_mkl_py3
microsoft/cntk2.6-gpu-python3.5-cuda9.0-cudnn7.0
chainer/chainerv6.0.0b1


if any question, welcome to leave message

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