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Merge pull request #553 from xiaodaigh/patch-2

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Updated with more detailed instructions for installing CuArrays
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Mike J Innes 2019-01-28 10:36:27 +00:00 committed by GitHub
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docs/src/gpu.md
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# GPU Support # GPU Support
## Installation
To get GPU support for NVIDIA graphics cards, you need to install `CuArrays.jl`
**Steps needed**
1. Install [NVIDIA toolkit](https://developer.nvidia.com/cuda-downloads)
2. Install [NVIDIA cuDNN library](https://developer.nvidia.com/cudnn)
3. In Julia's terminal run `]add CuArrays`
## GPU Usage
Support for array operations on other hardware backends, like GPUs, is provided by external packages like [CuArrays](https://github.com/JuliaGPU/CuArrays.jl). Flux is agnostic to array types, so we simply need to move model weights and data to the GPU and Flux will handle it. Support for array operations on other hardware backends, like GPUs, is provided by external packages like [CuArrays](https://github.com/JuliaGPU/CuArrays.jl). Flux is agnostic to array types, so we simply need to move model weights and data to the GPU and Flux will handle it.
For example, we can use `CuArrays` (with the `cu` converter) to run our [basic example](models/basics.md) on an NVIDIA GPU. For example, we can use `CuArrays` (with the `cu` converter) to run our [basic example](models/basics.md) on an NVIDIA GPU.