Enterprise & Cloud Benchmarks

Below you can find Intel's internal benchmarking numbers. The EPYC 7601 is the reference (performance=1), the 8160 is represented by the light blue bars, the top of the line 8180 numbers are dark blue. On a performance per dollar metric, it is the light blue worth observing.

Java benchmarks are typically unrealistically tuned, so it is a sign on the wall when an experienced benchmark team is not capable to make the Intel 8160 shine: it is highly likely that the AMD 7601 is faster in real life.

The node.js and PHP runtime benchmarks are very different. Both are open source server frameworks to generate for example dynamic page content. Intel uses a client load generator to generate a real workload. In the case of the PHP runtime, MariaDB (MySQL derivative) 10.2.8 is the backend.

In the case of Node.js, mongo db is the database. A node.js server spawns many different single threaded processes, which is rather ideal for the AMD EPYC processor: all data is kept close to a certain core. These benchmarks are much harder to skew towards a certain CPU family. In fact, Intel's benchmarks seem to indicate that the AMD EPYC processors are pretty interesting alternatives. Surely if Intel can only show a 5% advantage with a 10% more expensive processor, chances are that they perform very much alike in the real world. In that case, AMD has a small but tangible performance per dollar advantage.

The DPDK layer 3 Network Packet Forwarding is what most of us know as routing IP packets. This benchmark is based upon Intel own Data Plane Developer Kit, so it is not a valid benchmark to use for an AMD/Intel comparison.

We'll discuss the database HammerDB, NoSQL and Transaction Processing workloads in a moment.

The second largest performance advantage has been recorded by Intel testing the distributed object caching layer memcached. As Intel notes, the benchmark was not a processing-intensive workload, but rather a network-bound workload. As AMD's dual socket system is seen as a virtual 8-socket system, due to the way that AMD has put four dies onto each processor and each die has a sub-set of PCIe lanes linked to it, AMD is likely at a disadvantage.

Intel's example of network bandwidth limitations in a pseudo-socket configuration

Suppose you have two NICs, which is very common. The data of the first NIC will, for example, arrive in NUMA node 1, Socket 1, only to be accessed by NUMA node 4, Socket 1. As a result, there is some additional latency incurred. In Intel's case, you can redirect a NIC to each socket. With AMD, this has to be locally programmed, to ensure that the packets that are sent to each NICs are processed on each virtual node, although this might incur additional slowdown.

The real question is whether you should bother to use a 2S system for Memached. After all, it is distributed cache layer that scales well over many nodes, so we would prefer a more compact 1S system anyway. In fact, AMD might have an advantage as in the real world, Memcached systems are more about RAM capacity than network or CPU bottlenecks. Missing the additional RAM-as-cache is much more dramatic than waiting a bit longer for a cache hit from another server.

The virtualization benchmark is the most impressive for the Intel CPUs: the 8160 shows a 37% performance improvement. We are willing to believe that all the virtualization improvements have found their way inside the ESXi kernel and that Intel's Xeon can deliver more performance. However, in most cases, most virtualization systems run out of DRAM before they run out of CPU processing power. The benchmarking scenario also has a big question mark, as in the footnotes to the slides Intel achieved this victory by placing 58 VMs on the Xeon 8160 setup versus 42 VMs on the EPYC 7601 setup. This is a highly odd approach to this benchmark.

Of course, the fact that the EPYC CPU has no track record is a disadvantage in the more conservative (VMware based) virtualization world anyway.

Competitive Analysis and Price Comparisons Database Performance & Variability
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  • lefty2 - Tuesday, November 28, 2017 - link

    When Skylake runs AVX 512 and AVX2 instructions it causes both the clock frequency to go down *and* the voltage to go up. (https://www.intel.com/content/dam/www/public/us/en... However, it can only bring the voltage back down within 1ms. If you get a mix of AVX2 and regular instructions, like you do in the POV ray test, then it's going to be running on higher voltage the whole time. That probably explains why the Xeon 8176 drawed so much more power than the EPYC in your Energy consumption test.
    The guys at cloudflare also observed a similar effect (although they only notice the performance degrade): https://blog.cloudflare.com/on-the-dangers-of-inte...
  • Kevin G - Tuesday, November 28, 2017 - link

    In the HPC section, the article indicates that NAMD is faster on the Epyc system but the accompanying graphic points toward a draw with the Xeon Gold 6148 and a win for the Xeon Platinum 8160. Epyc does win a few benchmarks in the list prior to NAMD though.
  • Frank_han - Tuesday, November 28, 2017 - link

    When you run those tests, have you bind CPU threads, how did you take care of different layers of numa domains.
  • UpSpin - Tuesday, November 28, 2017 - link

    HIghly questionable article:
    "A lot of time the software within a system will only vaguely know what system it is being run on, especially if that system is virtualised". Why do you say this if you publish HPC results? There the software knows exactly whay type of processor in what kind of configuration it is running.
    "The second is the compiler situation: in each benchmark, Intel used the Intel compiler for Intel CPUs, but compiled the AMD code on GCC, LLVM and the Intel compiler, choosing the best result" More important, what type of math library did they use? The Intel MKL has an unmatched optimization, have they used the same for the AMD system?
    "Firstly is that these are single node measurements: One 32-core EPYC vs 20/24-core Intel processors." Why don't you make it clear, that by doing this, the benchmark became useless!!! Performance doesn't scale linearly with core count: http://www.gromacs.org/@api/deki/files/240/=gromac...
    So it makes a huge difference if I compare a simulation which runs on 32 cores with a simulation which runs on 20 cores. If I calculate the performance per core then, I always see that the lower core CPU is much much faster, because of scaling issues of the simulation software. You haven't disclosed how Intel got their 'relative performance' value.
  • Elstar - Tuesday, November 28, 2017 - link

    Do we know for sure that the Omni-Path Skylake CPUs actually use PCIe internally for the fabric port? If you look at Intel's "ark" database, all of the "F" parts have one fewer UPI links, which seems weird.
  • HStewart - Tuesday, November 28, 2017 - link

    I think this was a realistic article on analysis of the two systems. And it does point to important that Intel system is more mature system than AMD EPYC system. My personally feeling is that AMD is thrown together so that claim core count without realistically thinking about the designed.

    But it does give Intel a good shot in ARM with completion and I expect Intel's next revision to have significantly leap in technology.

    I did like the systems for similarly configured - as the cost, I build myself 10 years a dual Xeon 5160 that was about $8000 - but it was serious machine at the time and significantly faster than normal desktop and last much longer. It was also from Supermicro and find machine - for the longest time it was still faster than a lot machine you can get at BestBuy - it has Windows 10 on it now and still runs today - but I rarely used it because I like the portability of laptops
  • gescom - Tuesday, November 28, 2017 - link


    And suddenly - 8 core 6134 Skylake-SP - equals - 32 core Epyc 7601.
    Amazing. Really amazing.
  • gescom - Tuesday, November 28, 2017 - link

    Huh, I forgot - and that is Skylake at 130W vs Epyc at 180W.
  • ddriver - Tuesday, November 28, 2017 - link

    Gromacs is a very narrow niche product and also very biased - they heavily optimize for intel and nvidia and push amd products to take an inefficient code path.
  • HStewart - Tuesday, November 28, 2017 - link

    This is comparison with AVX2 / AVX512

    AVX512 is twice as wide as AVX2 and significant more power than the AVX2 - so yes it very possible in this this test that CPU with 1/4 the normal CPU cores can have more power because AVX512.

    Also I heard AMD's implementation of AVX2 is actually two 128 bits together - these results could show that is true.

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