The IBM POWER8 Review: Challenging the Intel Xeon
by Johan De Gelas on November 6, 2015 8:00 AM EST- Posted in
- IT Computing
- CPUs
- Enterprise
- Enterprise CPUs
- IBM
- POWER
- POWER8
Floating Point: C-ray
Shifting over from integer to floating point benchmarks we have C-ray. C-ray is an extremely simple ray-tracer which is not representative of any real world raytracing application. In fact, it is essentially a floating point benchmark that runs out the L1-cache. Luckily it is not as synthetic and meaningless as Whetstone, as you can actually use the software to do simple raytracing. That is not the kind of benchmark we like to use for the evaluations of server CPUs, but since our first efforts to port some of our favorite applications to OpenPOWER failed, we settled for something easier. We knew we would have the POWER8 system only for a few weeks, so we had to play it safe.
First we compiled the C-ray multi-threaded version with -O3 -ffast-math. To understand the CPU performance better, we limited C-ray with taskset to one or two threads (CPU 0 and 18) on the Haswell-based Xeon and one to eight threads on the POWER8. We also kept the output resolution at 768x432 to keep the render times in check. The "sphfract" file was used as input.
Real floating point intensive applications tend to put the memory subsystem under pressure, and running a second thread makes it only worse. So we are used to seeing that many HPC applications performe worse with multi-threading on. But since C-ray runs mostly out of the L1-cache, we get different behavior. Still, 8 threads of floating action seem to be too much: the POWER8 delivers the best FP performance at 4 threads. At this point, the POWER8 core is able to deliver 20% higher floating point performance than the Haswell Xeon.
Next we used all 160 (20 x 8 threads SMT) or 72 (36 x 2 threads SMT) threads and increased the resolution to 3840x2160.
With a core count that is 80% higher, there is nothing stopping the Xeon E5-2699 v3 from taking the top spot. Still, the POWER8 delivers solid performance and outperforms the slower Xeon E5-2695 v3 by 5%. Although the real world relevance of this benchmark is small, we now have an idea of how good the "basic FP" performance is. Otherwise in real world applications, the use of AVX-2/VSX and the available bandwidth will play a role.
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usernametaken76 - Thursday, November 12, 2015 - link
Technically this is not true. IBM had a working version of AIX running on PS/2 systems as late as the 1.3 release. Unfortunately support was withdrawn and future releases of AIX were not compiled for x86 compatible processors. One can still find a copy of this release if one knows where to look. It's completely useless to anyone but a museum or curious hobbyist, but it's out there.zenip - Friday, November 13, 2015 - link
...>--click here-Steven Perron - Monday, November 23, 2015 - link
Hello Johan,I was reading this article, and I found it interesting. Since I am a developer for the IBM XL compiler, the comparisons between GCC and XL were particularly interesting. I tried to reproduce the results you are seeing for the LZMA benchmark. My results were similar, but not exactly the same.
When I compared GCC 4.9.1 (I know a slightly different version that you) to XL 13.1.2 (I assume this is the version you used), I saw XL consistently ahead of GCC, even when I used -O3 for both compilers.
I'm still interested in trying to reproduce your results, so I can see what XL can do better, so I have a couple questions on areas that could be different.
1) What version of the XL compiler did you use? I assumed 13.1.2, but it is worth double checking.
2) Which version of the 7-zip software did you use? I picked up p7zip 15.09.
3) Also, I noticed when the Power 8 machine was running at full capacity (for me that was 192 threads on a 24 core machine), the results would fluctuate a bit. How many runs did you do for each configuration? Were the results stable?
4) Did you try XL at the less aggressive and more stable options like "-O3" or "-O3 -qhot"?
Thanks for you time.
Toyevo - Wednesday, November 25, 2015 - link
Other than the ridiculous price of CDIMMs the power efficiency just doesn't look healthy. For data centers leasing their hardware like Amazon AWS, Google AppEngine, Azure, Rackspace, etc, clients who pay for hardware yet fail to use their allocation significantly help the bottom line of those companies by reduced overheads. For others high usage is a mandatory part of the ROI equation during its period as an operating asset, thus power consumption is a real cost. Even with our small cluster of 12 nodes the power efficiency is a real consideration, let alone companies standardizing toward IBM and utilising 100s or 1000s of nodes that are arguably less efficient.Perhaps you could devise some sort of theoretical total cost of ownership breakdown for these articles. My biggest question after all of this is, which one gets the most work done with the lowest overheads. Don't get me wrong though, I commend you and AnandTech on the detail you already provide.
AstroGuardian - Tuesday, December 8, 2015 - link
It's good to have someone challenging Intel, since AMD crap their pants on regular basisdba - Monday, July 25, 2016 - link
Dear Johan:Can you extrapolate how much faster the Sparc S7 will be in your Cluster Benchmarking,
if the 2 on Die Infiniband ports are Activated, 5, 10, 20% ???
Thank You, dennis b.