AMD's EPYC Server CPU

If you have read Ian's articles about Zen and EPYC in detail, you can skip this page. For those of you who need a refresher, let us quickly review what AMD is offering. 

The basic building block of EPYC and Ryzen is the CPU Complex (CCX), which consists of 4 vastly improved "Zen" cores, connected to an L3-cache. In a full configuration each core technically has its own 2 MB of L3, but access to the other 6 MB is rather speedy. Within a CCX we measured 13 ns to access the first 2 MB, and 15 to 19 ns for the rest of the 8 MB L3-cache, a difference that's hardly noticeable in the grand scheme of things. The L3-cache acts as a mostly exclusive victim cache. 

Two CCXes make up one Zeppelin die. A custom fabric – AMD's Infinity Fabric – ties together two CCXes, the two 8 MB L3-caches, 2 DDR4-channels, and the integrated PCIe lanes. That topology is not without some drawbacks though: it means that there are two separate 8 MB L3 caches instead of one single 16 MB LLC. This has all kinds of consequences. For example the prefetchers of each core make sure that data of the L3 is brought into the L1 when it is needed. Meanwhile each CCX has its own separate (not inside the L3, so no capacity hit) and dedicated SRAM snoop directory (keeping track of 7 possible states). In other words, the local L3-cache communicates very quickly with everything inside the same CCX, but every data exchange between two CCXes comes with a tangible latency penalty. 

Moving further up the chain, the complete EPYC chip is a Multi Chip Module(MCM) containing 4 Zeppelin dies.

AMD made sure that each die is only one hop apart from the other, ensuring that the off-die latency is as low as reasonably possible.

Meanwhile scaling things up to their logical conclusion, we have 2P configurations. A dual socket EPYC setup is in fact a "virtual octal socket" NUMA system. 

AMD gave this "virtual octal socket" topology ample bandwidth to communicate. The two physical sockets are connected by four bidirectional interconnects, each consisting of 16 PCIe lanes. Each of these interconnect links operates at +/- 38 GB/s (or 19 GB/s in each direction). 

So basically, AMD's topology is ideal for applications with many independently working threads such as small VMs, HPC applications, and so on. It is less suited for applications that require a lot of data synchronization such as transactional databases. In the latter case, the extra latency of exchanging data between dies and even CCX is going to have an impact relative to a traditional monolithic design.

Tensions (And Chip Sizes) Are Rising AMD’s EPYC 7000-Series Processors
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  • coder543 - Tuesday, July 11, 2017 - link

    Right, of course. Ryzen is a copy-and-paste of Haswell.

    Don't make me laugh.
    Reply
  • psychobriggsy - Tuesday, July 11, 2017 - link

    Indeed it is a ridiculous comment, and puts the earlier crying about the older Ubuntu and GCC into context - just an Intel Fanboy.

    In fact Intel's core architecture is older, and GCC has been tweaked a lot for it over the years - a slightly old GCC might not get the best out of Skylake, but it will get a lot. Zen is a new core, and GCC has only recently got optimisations for it.
    Reply
  • EasyListening - Wednesday, July 12, 2017 - link

    I thought he was joking, but I didn't find it funny. So dumb.... makes me sad. Reply
  • blublub - Tuesday, July 11, 2017 - link

    I kinda miss Infinity Fabric on my Haswell CPU and it seems to only have on die - so why is that missing on Haswell wehen Ryzen is an exact copy? Reply
  • blublub - Tuesday, July 11, 2017 - link

    Your actually sound similar to JuanRGA at SA Reply
  • Kevin G - Wednesday, July 12, 2017 - link

    @CajunArson The cache hierarchy is radically different between these designs as well as the port arrangement for dispatch. Scheduling on Ryzen is split between execution resources where as Intel favors a unified approach. Reply
  • bill.rookard - Tuesday, July 11, 2017 - link

    Well, that is something that could be figured out if they (anandtech) had more time with the servers. Remember, they only had a week with the AMD system, and much like many of the games and such, optimizing is a matter of run test, measure, examine results, tweak settings, rinse and repeat. Considering one of the tests took 4 hours to run, having only a week to do this testing means much of the optimization is probably left out.

    They went with a 'generic' set of relative optimizations in the interest of time, and these are the (very interesting) results.
    Reply
  • CoachAub - Wednesday, July 12, 2017 - link

    Benchmarks just need to be run on as level as a field as possible. Intel has controlled the market so long, software leans their way. Who was optimizing for Opteron chips in 2016-17? ;) Reply
  • theeldest - Tuesday, July 11, 2017 - link

    The compiler used isn't meant to be the the most optimized, but instead it's trying to be representative of actual customer workloads.

    Most customer applications in normal datacenters (not google, aws, azure, etc) are running binaries that are many years behind on optimizations.

    So, yes, they can get better performance. But using those optimizations is not representative of the market they're trying to show numbers for.
    Reply
  • CajunArson - Tuesday, July 11, 2017 - link

    That might make a tiny bit of sense if most of the benchmarks run were real-world workloads and not C-Ray or POV-Ray.

    The most real-world benchmark in the whole setup was the database benchmark.
    Reply

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