Although the AMD EPYC is definitely a worthy contender in the server space, AMD's technical marketing of the new CPU has been surprisingly absent, as the company not published any real server benchmarks. The only benchmarks published were SPEC CPU and Stream, with AMD preferring for its partners and third parties to promote performance. And, as our long-time readers know, while the SPEC CPU benchmarks have their merits and many people value them, they are a very poor proxy of most server workloads.

In every launch, we expect companies to offer an element of competitive analysis, often to show how their platform is good or better than the rest. At the launch of Intel's latest Xeon-SP platform, analysis to EPYC was limited to a high-level, as the systems were not as freely available as expected. AMD was able to do so on Broadwell-E at the time of the EPYC announcement because it was out and available - Intel wasn't able to do it on EPYC because AMD were several months away from moving it from a cloud-only ramp up program. This is partly the effect of AMD's server market implementation and announcement roadmap, although it didn't stop Intel from hypothesising about the performance deficits in ways that caught the attention of a number of online media.

Throughout all of this, AMD could not resist but to continue to tell the world that the "EPYC SoC Sets World Records on SPEC CPU Benchmarks". In the highly profitable field that is server hardware, this could not be left unanswered by Intel, who responded that the Intel Xeon Scalable has great "momentum" with no less than 110 performance records to date. 

Jumping to the present time, in order to to prove Xeon-SP dominance over the competition, Intel's data center engineering group has been able to obtain a few EPYC systems and has started benchmarking. This benchmarking, along with justifications of third-party verification, was distributed to the small set of Xeon-SP launch reviewers as a guide, to follow up on that high-level discussion some time ago. The Intel benchmarking document we received had a good amount of detail however, and the conference call we had relating to it was filled with some good technical tidbits.

Our own benchmarks showed that the EPYC was a very attractive alternative in some workloads (Java applications), while the superior mesh architecture makes Intel's Xeon the best choice in other (Databases for example).

A Side Note About SPEC

A number of these records were achieved through SPEC. As mentioned above, while SPEC is a handy tool for comparing the absolute best tweaked peak performance of the hardware underneath, or if the system wants to be analysed close to the metal because of how well known the code base is, but this has trouble transferring exactly to the real world. 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. Sending AVX-512 commands down the pipe is one thing, but SPEC compilation can be tweaked to make sure that cache locality is maintained whereas in the real-world, that might not be possible. SPEC says a lot about the system, but ultimately most buyers of these high-end systems are probing real-world workloads on development kits to see what their performance (and subsequent scale-out performance) might be.

For the purposes of this discussion, we have glossed over Intel's reported (and verified over at SPEC.org) results.

Pricing Up A System For Comparison

Professionals and the enterprise market will mention, and quite rightly, that Intel has been charging some heavy premiums with the latest generation, with some analysts mentioning a multiple jump up in pricing even for large customers, making it clear that the Xeon enterprise CPU line is their bread and butter. Although Intel's top-end Xeon Platinum 8180 should give the latest EPYC CPU a fit of trouble thanks to its 28 Skylake-SP cores running at 2.5 to 3.8 GHz, the massive price tag ($10009 for the standard version, $13011 for the high-memory model) made sure that Intel's benchmarking team had no other choice than also throwing in a much more modest Xeon Platinum 8160 (24 cores at 2.1 - 3.7 GHz, $4702k) as well as the Xeon Gold 6148 (20 cores at 2.4-3.7 GHz, $3072).

SKUS Tested
  Intel Xeon
Platinum 8180
Intel Xeon
Platinum 8160
Intel Xeon
Gold 6148
  AMD
EPYC 7601
Release Date Early Q3, 2017   Late Q2, 2017*
Microarchitecture Skylake-SP with AVX-512   Zen
Process Node Intel 14nm (14+)   GloFo 14nm
 
Cores / Threads 28 / 56 24 / 48 20 / 40   32 / 64
Base Frequency 2.5 GHz 2.1 GHz 2.4 GHz   2.2 GHz
Turbo 3.8 GHz 3.7 GHz 3.7 GHz   3.2 GHz
L2 Cache 28 MB 24 MB 20 MB   16 MB
L3 Cache 38.5 MB 33.0 MB 27.5 MB   64 MB
TDP 205 W 150 W 150 W   180 W
PCIe Lanes 48 (Technically 64 w/ Omni-Path Versions)   128
DRAM 6-channel DDR4   8ch DDR4
Max Memory 768 GB   2048 GB
Price $10009 $4702 $3072   $4200

As a result of this pricing, one of the major humps for Intel in any comparison will be performance per dollar. In order to demonstrate that systems can be equivalent, Intel offered up this comparison from a single retailer. Ideally Intel should have offered multiple configurations options for this comparison, given that a single retailer can intend for different margins on different sets of products (or have different levels of partnership/ecosystem with the manufacturers).

Even then, price parity could only be reached by giving the Intel system less DRAM. Luckily this was the best way to configure the Intel based system anyway. We can only guess how much the benchmarking engineers swore at the people who set the price tags: "this could have been so much easier...". All joking apart, the document we received had a good amount of detail, and similar to how we looked into AMD's benchmarking numbers at their launch, we investigated Intel's newest benchmark numbers as well.

Enterprise & Cloud Benchmarks
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  • beginner99 - Tuesday, November 28, 2017 - link

    CPU price or server price are almost always irrelevant because the software running on them costs at least an order of magnitude more than the hardware itself. So you get the fastest server you need / the software profits from. Reply
  • ddriver - Tuesday, November 28, 2017 - link

    Not necessarily, there is a lot of free and opensource software that is enterprise-capable.

    Also "the fastest server" actually sell in very small quantities. Clearly the cpu cost is not irrelevant as you claim. And clearly if it was irrelevant, intel would not even bother offering low price skus, which actually constitute the bulk of it sales, in terms of quantity as well as revenue.
    Reply
  • yomamafor1 - Tuesday, November 28, 2017 - link

    128GB for 32 core is suspiciously low.... For that kind of core count, generally the server has 512GB or above.

    Also, 128GB of memory in this day and age is definitely not $1,500 tops. Maybe in early 2016, but definitely not this year, and definitely not next year.

    And from what I've seen, the two biggest cost factors in an enterprise grade server is the SSDs and memory. Generally memory accounts for 20% of the server cost, while SSD accounts for about 30%.

    CPU generally accounts for 10% of the cost. Not insignificant, but definitely not "makes up half of the machine's budget".

    AMD has a very hard battle to get back into the datacenter. Intel is already competing aggressively.
    Reply
  • ddriver - Tuesday, November 28, 2017 - link

    Care to share with us your "correct ram amount per cpu core" formula? There I was, thinking that the amount of ram necessary was determined by the use case, turns out it is a product of core count. Reply
  • bcronce - Tuesday, November 28, 2017 - link

    In general a server running VMs is memory limited well before CPU limited. Reply
  • ddriver - Tuesday, November 28, 2017 - link

    Not necessarily. It depends on what kind of work will those VMs be doing. Visualized or bare metal, configuration details are dictated by the target use case. Sure, you can also build universal machines and cram them full of as much cores and memory they can take, but that is very cost ineffective.

    I can think of a usage scenario that will be most balanced with a quad core cpu and 1 terabyte of ram. Lots of data, close to no computation taking place, just data reads and writes. A big in-memory database server.

    I can think of a usage scenario that will be most balanced with a 32 core cpu and 64 gigabytes of ram. An average sized data set involved in heavy computation. A render farm node server.
    Reply
  • ddriver - Tuesday, November 28, 2017 - link

    *virtualized not visualized LOL, did way too many visualizations back in the day, hands now type on autopilot... Reply
  • yomamafor1 - Tuesday, November 28, 2017 - link

    It is certainly determined by the use cases, but after interacting with hundreds of companies and their respective workloads, generally higher core counts are mapped to higher memory capacity.

    Of course, there are always very few fringe use cases that focuses significantly on compute.
    Reply
  • Holliday75 - Saturday, December 09, 2017 - link

    What about large players like Microsoft Azure or AWS? I have worked with both and neither uses anything close to what you guys talk about in terms of RAM or CPU. Its all about getting the most performance per watt. When you data center has its own substation your electric bill might be kinda high. Reply
  • submux - Thursday, November 30, 2017 - link

    I will overlook the rudeness of your comment. I actively work with enterprise hardware and would probably not make comments like that and then recommend outfitting a server with 128GB of RAM. I don't think I've been near anything with as little as that in a long while. 128GB is circa 2012-2013.

    An enterprise needs 6 servers to ensure one operational node in a redundant environment. This is because in two data centers, you have 3 servers each. In case of a catastrophe, a full data center is lost and while a server is in maintenance and then finally another server fails. Therefore, you need precisely 6 servers to provide a reasonable SLA. 9 servers is technically more correct, in a proper 3 data center design.

    If you know anything about storage, you would prefer more servers as more servers provides better storage response times... unless you're using SAN which is pretty much reserved strictly to people who simply don't understand storage and are willing to forfeit price, performance, reliability, stability, etc... to avoid actually taking a computer science education.

    In enterprise IT, there are many things to consider. But for your virtualization platform, it's pretty simple. Fit as much capacity as possible in to as few U as possible while never dropping below 6 servers. Of course, I rarely work with less than 500 servers at a time, but I focus on taking messy 10,000+ server environments and shrinking them to 500 or less.

    See, each server you add adds cost to operation. This means man-hours. Storage costs. Degradation of performance in the fabrics, etc... it introduces meaningless complexity and requires IT engineers to waste more and more hours building illogical platforms more focused on technology than the business they were implemented for.

    If I approach a customer, I tend to let them know that unless they are prepared to invest at least $50,000 per server for 6 servers and $140,000 for the appropriate network, they should deploy using an IaaS solution (not cloud, never call IaaS cloud) where they can share a platform that was built to these requirements. The breaking point where IaaS is less economical than DIY is at about $500,000 with an OpEx investment of $400,000-$600,000 for power, connectivity, human resources, etc... annually and this doesn't even include having experts on the platform running on the data center itself.

    So with less than a minimum of $1 million a year investment in just providing infrastructure (VMware, Nutanix, KVM, Hyper-V), not even providing a platform to run on it, you're just pissing the wrong way in the wind tunnel and wasting obscene amounts of money for no apparent reason on dead-end projects run by people who spend money without considering the value provided.

    In addition, the people running your data center for that price are increasing in cost and their skillset is aging and decreasing in value over that time.

    I haven't even mentioned power, cooling, rack space, cabling, managed PDUs, electricians, plumbers, fire control, etc...

    Unless you're working with BIG DATA, an array of 2-4 TB drives for under $10,000 to feed even one 32-core AMD EPYC is such an insanely bad idea, it's borderline criminal stupidity. Let's not even discuss feeding pipelines of 6 32-core current generation CPUs per data center. It would be like trying to feed a blue whale with a teaspoon. In a virtualized configuration a deal EPYC server probably would need 100GB/s+ bandwidth to barely keep ahead of process starvation.

    If you have any interest at all in return on investment in enterprise IT, you really need to up your game to make it work on paper.

    Now... consider that if you're running a virtual data center... plain vanilla. Retail license cost of Windows Enterprise and VMware (vCenter, NSX, vSAN) for a dual 32-core EPYC is approximately $125,000 a server. Cutting back to dual 24-core with approximately the same performance would save about $30,000 a server in software alone.

    I suppose I can go on and on... but let's be pretty clear CajunArson made a fair comment and probably is considering the cost of 1-2TB per server of RAM. Not 128GB which is more of a graphics workstation in 2017.
    Reply

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