Floating Point

Normally our HPC benchmarking is centered around OpenFoam, a CFD software we have used for a number of articles over the years. However, since we moved to Ubuntu 16.04, we could not get it to work anymore. So we decided to change our floating point intensive benchmark for now. For our latest article, we're testing with C-ray, POV-Ray, and NAMD.

The idea is to measure:

  1. A FP benchmark that is running out of the L1 (C-ray)
  2. A FP benchmark that is running out of the L2 (POV-Ray)
  3. And one that is using the memory subsytem quite often (NAMD)

Floating Point: 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 of the L1-cache. Luckily it is not as synthetic and meaningless as Whetstone, as you can actually use the software to do simple raytracing.

We use the standard benchmarking resolution (3840x2160) and the "sphfract" file to measure performance. The binary was precompiled.

C-ray rendering at 3840x2160

Wow. What just happened? It looks like a landslide victory for the raw power of the four FP pipes of Zen: the EPYC chip is no less than 50% faster than the competition. Of course, it is easy to feed FP units if everything resides in the L1. Next stop, POV-Ray.

Floating Point: POV-Ray 3.7

The Persistence of Vision Raytracer (POV-Ray) is a well known open source raytracer. We compiled our version based upon the version that can be found on github (https://github.com/POV-Ray/povray.git). No special optimizations were done, we used "prebuild.sh", configure, make, and make install.

Povray

POV-Ray is known to run mostly out of the L2-cache, so the massive DRAM bandwidth of the EPYC CPU does not play a role here. Nevertheless, the EPYC CPU performance is pretty stunning: about 16% faster than Intel's Xeon 8176. But what if AVX and DRAM access come in to play? Let us check out NAMD.

Floating Point: NAMD

Developed by the Theoretical and Computational Biophysics Group at the University of Illinois Urbana-Champaign, NAMD is a set of parallel molecular dynamics codes for extreme parallelization on thousands of cores. NAMD is also part of SPEC CPU2006 FP. In contrast with previous FP benchmarks, the NAMD binary is compiled with Intel ICC and optimized for AVX.

First, we used the "NAMD_2.10_Linux-x86_64-multicore" binary. We used the most popular benchmark load, apoa1 (Apolipoprotein A1). The results are expressed in simulated nanoseconds per wall-clock day. We measure at 500 steps.

NAMD molecular dynamics

Again, the EPYC 7601 simply crushes the competition with 41% better performance than Intel's 28-core. Heavily vectorized code (like Linpack) might run much faster on Intel, but other FP code seems to run faster on AMD's newest FPU.

For our first shot with this benchmark, we used version 2.10 to be able to compare to our older data set. Version 2.12 seems to make better use of "Intel's compiler vectorization and auto-dispatch has improved performance for Intel processors supporting AVX instructions". So let's try again:

NAMD molecular dynamics 2.12

The older Xeons see a perforance boost of about 25%. The improvement on the new Xeons is a lot lower: about 13-15%. Remarkable is that the new binary is slower on the EPYC 7601: about 4%. That simply begs for more investigation: but the deadline was too close. Nevertheless, three different FP tests all point in the same direction: the Zen FP unit might not have the highest "peak FLOPs" in theory, there is lots of FP code out there that runs best on EPYC.

Big Data benchmarking Energy Consumption
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  • JKflipflop98 - Wednesday, July 12, 2017 - link

    For years I thought you were just really committed to playing the "dumb AMD fanbot" schtick for laughs. It's infinitely more funny now that I know you've actually been *serious* this entire time. Reply
  • ddriver - Wednesday, July 12, 2017 - link

    Whatever helps you feel better about yourself ;) I bet it is funny now, that AT have to carefully devise intel biased benches and lie in its reviews in hopes intel at least saves face. BTW I don't have a single amd CPU running ATM. Reply
  • WinterCharm - Thursday, July 13, 2017 - link

    Uh, what are you smoking? this is a pretty even piece. Reply
  • boozed - Tuesday, July 11, 2017 - link

    You haven't done your job properly unless you've annoyed the fanboys (and perhaps even fangirls) for both sides! Reply
  • JohanAnandtech - Wednesday, July 12, 2017 - link

    Wise words. Indeed :-) Reply
  • Ranger1065 - Wednesday, July 12, 2017 - link

    If you are referring to ddriver, I agree, wise words indeed. Reply
  • ddriver - Wednesday, July 12, 2017 - link

    Well, that assumption rests on the presumption that the point of reviews is to upsed fanboys.

    I'd say that a "review done right" would include different workload scenarios, there is nothing wrong with having one that will show the benefits of intel's approach to doing server chips, but that should be properly denoted, and should be just one of several database tests and should be accompanied by gigabytes of databases which is what we use in real world scenarios.
    Reply
  • CoachAub - Wednesday, July 12, 2017 - link

    It was mentioned more than once that this review was rushed to make a deadline and that the suite of benchmarks were not everything they wanted to run and without optimizations or even the usual tweaks an end-user would make to their system. So, keep that in mind as you argue over the tests and different scenarios, etc. Reply
  • ddriver - Thursday, July 13, 2017 - link

    It doesn't take a lot of time to populate a larger database so that you can make a benchmark that involves an actual real world usage scenario. It wasn't the "rushing" that prompted the choice of database size... Reply
  • mpbello - Friday, July 14, 2017 - link

    If you are rushing, you reduce scope and deliver fewer pieces with high quality instead of insisting on delivering a full set of benchmarks that you are not sure about its quality.
    The article came to a very strong conclusion: Intel is better for database scenarios. Whatever you do, whether you are rushing or not, you cannot state something like that if the benchmarks supporting your conclusion are not well designed.
    So I agree that the design of the DB benchmark was incredibly weak to sustain such an important conclusion that Intel is the best choice for DB applications.
    Reply

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