Version 8 (modified by 7 years ago) (diff) | ,
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CSC NVCUDA
This CSC module takes advantage of nvidia GPU's CUDA capability to parallelize the conversion process and speed things up. You may also consider using the OpenCL CSC module, which can also use the GPU and is more generic (not vendor specific), better tested and often faster.
csc_nvcuda
Installation
- you need to build xpra with the flag "
--with-csc_nvcuda
", since this module is not enabled by default. - you must use a sufficiently recent version of the
nvidia
video drivers, preferably obtained directly from nvidia, and not thenouveau
drivers (which you should probably remove). - the build file relies on the presence of a standard
pkgconfig
file to find the CUDA libraries and headers. nvidia does not provide one with the SDK, so you will need to create one. You can use this example cuda.pc as a template.
Links
- this module relies on PyCUDA
- supported GPUs
- original feature request ticket with more information: #384
- csc_nvcuda module source
Module Options
- choose the device used with:
XPRA_CUDA_DEVICE=N xpra ...
Where N
is the device ID.
- Use:
XPRA_CUDA_DEBUG=1 xpra ...
to get more information.
Attachments (1)
-
cuda.pc (230 bytes) - added by 7 years ago.
example pkgconfig file for cuda
Download all attachments as: .zip