[Cin] GIT checkin includes Cakewalk update + limited specialized hardware acceleration options.

Phyllis Smith phylsmith2017 at gmail.com
Sun Jun 16 22:07:56 CEST 2019

Today's GIT checkin includes:

- Cakewalk update
- Nvenc option for encoding/rendering hardware acceleration for computers
with Nvidia graphics for h264/h265.
- Cuda build option for systems that already have the Cuda software loaded
- with 2 demo plugins available.

More info on the hardware acceleration options follow.  Some testing done
on Fedora 29 and Leap 15, but not all possibilities have been tried.  I
would expect to see some fallout.

NVENC/NVDEC for Nvidia graphics board encoding and decoding will
automatically be built by way of the configure scripts.  But first, before
anyone gets too excited, let me just warn you that the ONLY encode codec
Nvidia chose to support is H264 and H265 with H265 available on just the
latest graphics boards (supposedly at least the ones with the Maxwell
chip).  Also included in the ffmpeg build is "nvdec" but we have not
figured out yet how this affects the hardware acceleration already in place
with the use of CIN_HW_DEV=vdpau.

Some information that was posted online 11/04/2018 -- "VDPAU falling away
into irrelevance but no clear statements that consumers should switch to
nvdec or that nvidia will advance VDPAU feature parity.  ...All of these
things make it hard to see what the correct way to approach nvidia support
is, and even if you pick one, you can't actually integrate in a simple way."

The easiest way to determine if nvenc is working for you is just to do a
short render using h264_nvenc.mp4 or h265_nvenc.mp4 and see if it works or
just gives you an error message.  Error message for computers without nvdia
cards (or not implemented) is:   Cannot load libcuda.so.1    on the window
from where your started cin. BTW this libcuda is part of nvidia libraries
in the Operating System and does not mean you have CUDA in.

A 2 minute demo from Big Buck Bunny 3804x2160, took 6 minutes 3 seconds
with nvenc to render as opposed to 22 minutes 30 seconds without nvenc --
so not quite 4 times faster and I had no plugins added on a 4 core Intel
laptop with an Nvidia 950M graphics board.

CUDA® is a parallel computing platform / programming model that provides
big increases in computing performance through use of the GPU, graphics
processing unit. It was first introduced in about 2006 for applications in
computationally intense fields such as astronomy, biology, chemistry, and

The use of Cuda is not going to improve the playing and rendering of video
in Cinelerra EXCEPT in the case where you use a specific CUDA-enabled
plugin that is computationally intense - sadly, most of what Cin does, Cuda
will not help.  Cuda is mostly a "block oriented algorithm" which works
well for such things as "a flock of birds all flying next to each other".

If you have already installed the Cuda software on your computer -- and let
me warn you, this is about 3GB of additional space usage -- the default
build in the configure script is for cuda is "auto".  Otherwise it will NOT
be included.  Obviously, you must have the Nvdia drivers for your graphics
board installed too.  Cuda is available to install on your computer only
for a specific set of Operating System distros.  Go to the following


and gg says follow the very good set of directions to install around 3 GB.
It installs repos by package.  Also, install the "fusion repo" -- we do not
know if this needs to be installed or not, but all of our test included it.

I will attempt to create a demo a little later and there will most likely
be a Ubuntu16 and Mint18 build available soon for testing purposes.
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