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Results: Adobe CC

Intel Xeon E5-2600 v2: More Cores, Cache, And Better Efficiency
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Today’s story forces us to consider one consequence of a growing emphasis on heterogeneous computing. As we offload parallel tasks to on-die or discrete graphics engines, there’s less for many-core CPUs to do.

Although it’s tempting to look at our results and assume that CUDA acceleration is helping normalize performance as the Quadro FX 1800 becomes a bottleneck, Nvidia’s older pro board isn’t on Adobe’s list of supported add-in cards. We double-checked and verified that there is no GPU activity during the test; it’s CPU-only.

We also know from past stories that our Premiere Pro rendering tasks do utilize many cores. It’s probable that our benchmark isn’t complex enough to fully demonstrate what two eight-core processors can do. The Paladin test we used previously was intensive, but designed for Premiere Pro CS5. Two generations later, our Hollywood sequence just isn’t the same.

The same goes for After Effects, which can be accelerated by CUDA/OpenCL-compatible cards, but doesn’t natively support our Quadro FX 1800. In the past, this test was actually bottlenecked by three QuickTime clips, which couldn’t be threaded. We replaced those with PNG sequences to address that limitation. Now we see 100% utilization, though scaling is not evident based on host processor performance.

Finally, by the time we get to Photoshop CC, OpenCL support is enabled on our Quadro FX 1800. Interestingly, though, backing the Nvidia card with more x86 cores doesn’t help improve the performance of accelerated filters. In fact, the opposite is true: both dual-CPU workstations are slower than the Core i7-based box.

The situation reverses when we execute a series of threaded filters. The two Xeon E5-2687W v2s do their job in half the time of one Core i7-4960X. Chalk this up as an application where it pays to know where to spend money on hardware. Certain filters are going to push mainstream CPUs with high clock rates. Others will favor massively parallel configurations. And a few more are optimized for OpenCL.

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