Single Threaded Integer Performance: SPEC CPU2006

Even in the server market where high core count CPUs are ruling the roost, high single threaded performance is still very desirable. It makes sure that a certain level of performance is guaranteed in every situation, not just in "throughput situations" of "embarrassingly parallel" software. 

SPEC CPU2017 has finally launched, but it did so while our testing was already under way. So SPEC CPU2006 was still our best option to evaluate single threaded performance. Even though SPEC CPU2006 is more HPC and workstation oriented, it contains a good variety of integer workloads.

It is our conviction that we should try to mimic how performance critical software is compiled instead of trying to achieve the highest scores. To that end, we:

  • use 64 bit gcc : by far the most used compiler on linux for integer workloads, good all round compiler that does not try to "break" benchmarks (libquantum...) or favor a certain architecture
  • use gcc version 5.4: standard compiler with Ubuntu 16.04 LTS. (Note that this is upgraded from 4.8.4 used in earlier articles)
  • use -Ofast -fno-strict-aliasing optimization: a good balance between performance and keeping things simple
  • added "-std=gnu89" to the portability settings to resolve the issue that some tests will not compile with gcc 5.x
  • run one copy of the test

The ultimate objective is to measure performance in non-"aggressively optimized" applications where for some reason – as is frequently the case – a "multi-thread unfriendly" task keeps us waiting. 

First the single threaded results. It is important to note that thanks to modern turbo technology, all CPUs will run at higher clock speeds than their base clock speed. 

  • The Xeon E5-2690 ("Sandy Bridge") is capable of boosting up to 3.8 GHz
  • The Xeon E5-2690 v3 ("Haswell") is capable of boosting up to 3.5GHz
  • The Xeon E5-2699 v4  ("Broadwell") is capable of boosting up to 3.6 GHz
  • The Xeon 8176 ("Skylake-SP") is capable of boosting up to 3.8 GHz
  • The EPYC 7601 ("Naples") is capable of boosting up to 3.2 GHz

First we look at the absolute numbers. 

Subtest Application type Xeon E5-2690
@ 3.8
Xeon E5-2690 v3
@ 3.5
Xeon E5-2699 v4
@ 3.6
EPYC 7601
@3.2
Xeon 8176
@3.8
400.perlbench Spam filter 35 41.6 43.4 31.1 50.1
401.bzip2 Compression 24.5 24.0 23.9 24.0 27.1
403.gcc Compiling 33.8 35.5 23.7 35.1 24.5
429.mcf Vehicle scheduling 43.5 42.1 44.6 40.1 43.3
445.gobmk Game AI 27.9 27.8 28.7 24.3 31.0
456.hmmer Protein seq. analyses 26.5 28.0 32.3 27.9 35.4
458.sjeng Chess 28.9 31.0 33.0 23.8 33.6
462.libquantum Quantum sim 55.5 65.0 97.3 69.2 102
464.h264ref Video encoding 50.7 53.7 58.0 50.3 67.0
471.omnetpp Network sim 23.3 31.3 44.5 23.0 40.8
473.astar Pathfinding 25.3 25.1 26.1 19.5 27.4
483.xalancbmk XML processing 41.8 46.1 64.9 35.4 67.3

As raw SPEC scores can be a bit much to deal with in a dense table, we've also broken out our scores on a percentage basis. Sandy Bridge EP (Xeon E5 v1) is about 5 years old, the servers based upon this CPU are going to get replaced by newer ones. So we've made "Single threaded Sandy Bridge-EP performance" our reference (100%) , and compare the single threaded performance of all other architectures accordingly.

Subtest Application type Xeon E5-2690
@ 3.8
Xeon E5-2690 v3
@ 3.5
Xeon E5-2699 v4 @ 3.6 EPYC 7601 @3.2 Xeon 8176 @ 3.8
400.perlbench Spam filter 100% 119% 124% 89% 143%
401.bzip2 Compression 100% 98% 98% 98% 111%
403.gcc Compiling 100% 105% 70% 104% 72%
429.mcf Vehicle scheduling 100% 97% 103% 92% 100%
445.gobmk Game AI 100% 100% 103% 87% 111%
456.hmmer Protein seq. analyses 100% 106% 122% 105% 134%
458.sjeng Chess 100% 107% 114% 82% 116%
462.libquantum Quantum sim 100% 117% 175% 125% 184%
464.h264ref Video encoding 100% 106% 114% 99% 132%
471.omnetpp Network sim 100% 134% 191% 99% 175%
473.astar Pathfinding 100% 99% 103% 77% 108%
483.xalancbmk XML processing 100% 110% 155% 85% 161%

SPEC CPU2006 analysis is complicated, and with only a few days spend on the EPYC server, we must admit that what follows is mostly educated guessing. 

First off, let's gauge the IPC efficiency of the different architectures. Considering that the EPYC core runs at 12-16% lower clockspeeds (3.2 vs 3.6/3.8 GHz), getting 90+% of the performance of the Intel architectures can be considered a "strong" (IPC) showing for the AMD "Zen" architecture. 

As for Intel's latest CPU, pay attention to the effect of the much larger L2-cache of the Skylake-SP core (Xeon 8176) compared to the previous generation "Broadwell". Especially perlbench, gobmk, hmmer and h264ref (the instruction part) benefit. 

Meanwhile with the new GCC 5.4 compiler, Intel's performance on the "403.gcc benchmark" seems to have regressed their newer rchitectures. While we previously saw the Xeon E5-2699v4 perform at 83-95% of the "Sandy Bridge" Xeon E5-2690, this has further regressed to 70%. The AMD Zen core, on the other hand, does exceptionally well when running GCC. The mix of a high percentage of (easy to predict) branches in the instruction mix, a relatively small footprint, and a heavy reliance on low latency (mostly L1/L2/8 MB L3) seems to work well. The workloads where the impact of branch prediction is higher (somewhat higher percentage of branch misses) - gobmk, sjeng, hmmer - perform quite well on "Zen" too, which has a much lower branch misprediction penalty than AMD's previous generation architecture thanks to the µop cache. 

Otherwise the pointer chasing benchmarks – XML procesing and Path finding – which need a large L3-cache, are the worst performing on EPYC. 

Also notice the fact that the low IPC omnetpp ("network sim") runs slower on Skylake-SP than on Broadwell, but still much faster than AMD's EPYC. Omnetpp is an application that benefited from the massive 55 MB L3-cache of Broadwell, and that is why performance has declined on Skylake. Of course, this also means that the fractured 8x8 MB L3 of AMD's EPYC processor causes it to perform much slower than the latest Intel server CPUs. In the video encoding benchmark "h264ref" this plays a role too, but that benchmark relies much more on DRAM bandwidth. The fact that the EPYC core has higher DRAM bandwidth available makes sure that the AMD chip does not fall too far behind the latest Intel cores. 

All in all, we think we can conclude that the single threaded performance of the "Zen architecture" is excellent, but it somewhat let down by the lower turbo clock and the "smaller" 8x8 MB L3-cache. 

Memory Subsystem: Latency SMT Integer Performance With SPEC CPU2006
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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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