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Re: About the new Mac Pro-X

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Walter Soyka
Re: About the new Mac Pro-X
on Jun 16, 2013 at 5:00:53 am

[Marcus Moore] "I believe I've read from you that Motion and FCPX particularly will benefit from this- where GPUs power is more important than CPU cores. "

Yes. I think there are a number of applications which will benefit from the system design of the new Mac Pro, FCPX/M5 among them.

[Marcus Moore] "I haven't looked into this in a while, but its no longer as simple as GPUs are real-time performance and CPUs are for rendering, is it? My impression is that line has started to blur, even if its only in one direction with rendering being aided by GPUs now."

Absolutely. For a long time, rendering on a GPU meant rendering with OpenGL (Open Graphics Library) and one of the biggest benefits was the fact that it could render in real-time.

Now, rendering on a GPU goes well beyond graphics -- CUDA (Compute Unified Device Architecture) and OpenCL (Open Computing Language) both allow GPUs with their massively parallel architectures to crunch numbers instead of just draw images.

That means that you are not restricted to what's possible with OpenGL: you can implement other kinds of renderers and use the GPU to run the calculations.

The blurring is bi-directional, too. It's absolutely possible to use OpenGL for non-realtime rendering. Things like computing motion blur (basically rendering subframes and compositing them together), anti-aliasing (smoothing harsh edges of renders), and supersampling (a specific method of anti-aliasing where the images is rendered at higher resolution than output) can all slow a detailed OpenGL render to below real-time.

[Marcus Moore] "Where is the benefit to 24 cores now? 3D applications I'm guessing?"

Any CPU-heavy parallel task. 3D rendering is particularly notable, as there are few GPU-accelerated production renderers on the market and most renderers are still entirely CPU-based. Compositing is another: both Ae and NUKE benefit from loads of cores. Compression is a third: few encoders or decoders leverage GPUs.

These may be good candidates for GPU acceleration, but we're not there yet.

RAM-heavy uses (again, compositing is a good example) or operations on very large data sets tend to benefit from CPU rather than GPU, because very few GPUs have significant quantities of their own RAM.

[Marcus Moore] "Benchmarks tests for this thing are going to be interesting."

Yes indeed -- but in the end, I think it will come down to what software you want to use.

Walter Soyka
Principal & Designer at Keen Live
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