SPEC - MT Performance (4xlarge 16 vCPU)

The 64-core results were quite interesting and put the Graviton2 in a very competitive performance position, but all this talk about performance scaling varying depending on the loaded core count of the system made me wonder how the EC2 instances would perform at lower vCPU counts.

I fired up the same tests, just this time around with only rate-16 to match the number of vCPUs. These are 4xlarge EC2 instances with corresponding 16 vCPUs, but there’s one large caveat in this comparison that we must keep in mind: The Graviton2 instances very likely have no neighbours at this point in time in the test preview, meaning the performance scaling we’re seeing here is very much a best-case scenario for the Amazon chip. EC2 global capacity floats around at 60% active usage, and I imagine Amazon distributes this horizontally across the available sockets in their datacentres. How these performance figures will look like in the real world once Graviton2 ramps up in public availability is anybody’s guess.

The AMD system likely won’t care too much about such scenarios as their NUMA nature means they’re isolated from noisy neighbours anyhow, and we’re just seeing use of a single 8-core chip with its own memory controllers, but the Intel system will have possibly some neighbours doing some activity on the same socket and shared resources. I only ran one test run here; you’d probably need a lot of data to get a representative figure across EC2 usage.

For the Intel m5n instances, using an 4xlarge instance actually means you're only on on single socket this time around, meaning that the scaling behaviour in favour of higher per-thread performance isn't to be expected as high as on the Graviton2 system, as system DRAM bandwidth and L3 is halved compared to the 16xlarge figures on the previous page.

Also, since we’re testing 16 vCPU setups here, we can have an apples-to-apples comparison between the first- and second-generation Graviton systems which should be a fun comparison.

SPECint2006 Rate Estimated Scores (16 vCPU)

The comparison between the two generations of Graviton processors here is also astounding. Memory intensive workloads favour the newer Graviton2 by at least a factor of 2x, more often 3x, 4x, 5x and even up to 7x in libquantum.

The AMD system as expected doesn’t gain much scaling from using less cores as there’s no more shared resources available on a per-thread basis. The Intel chip fares slightly better per-thread, but doesn’t see the same higher performance scaling (Or should I say, reverse-scaling) as achieved by the Graviton2.

SPECfp2006(C/C++) Rate Estimated Scores (16 vCPU)

In fp2006, we see more or less the same kind of results.

SPEC2006 Rate-16 Estimated Total (4xlarge)

Overall, in the 16-vCPU rate results the Graviton2 surpasses the performance advantage it showcased in the 64-core results, ending up with an even bigger margin.

SPECint2017 Rate Estimated Scores (16 vCPU) SPECfp2017 Rate Estimated Scores (16 vCPU) SPEC2017 Rate-16 Estimated Total (4xlarge)

The SPEC2017 results again show the same conclusion – the Graviton2 really gains a ton of per-thread performance through the ability to use more of the chip’s L3 cache and 8 memory channels. Whilst on the 64-rate results the Graviton2 and the Xeon were neck-in-neck in fp2017, here the Graviton ends up with a 44% performance advantage.

Again, I can’t put enough emphasis on this, but these results are a best-case scenario for the 4xlarge 16vCPU results of the Graviton2. If production instances are able to achieve such figures will very largely depend on the draw of luck on whether you’re going to be alone on the physical hardware or whether you’ll have any neighbours on the chip. And even if you have neighbours, the performance figures will largely depend on what kind of workloads they will be running alongside your use-cases.

I saw a few articles out there comparing the performance between the m6g instances against the m5 generation instances (Skylake-SP hardware), but most of these tests were done only on medium (1 vCPU) to xlarge (4 vCPUs). When reading such pieces, it’s naturally important to keep in mind the vast scaling advantage the Graviton2 chip has – the smaller your instance is the more chance you’ll have noisy neighbours on the hardware, something that currently just doesn’t happen in the Graviton2’s preview phase.

SPEC - MT Performance (16xlarge 64vCPU) Cost Analysis - An x86 Massacre
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  • eek2121 - Tuesday, March 10, 2020 - link

    It is worth noting AnandTech’s own numbers: https://www.anandtech.com/show/14694/amd-rome-epyc... Reply
  • RallJ - Tuesday, March 10, 2020 - link

    I understand that, but consider everything boils down to just $/vCPU/hr, I think a discussion around the new Xeon Gold R is warranted. For example, the existing dual-socket Xeon Amazon is using can be substituted by the new 6248R for 60% lower price while providing a modest turbo and base frequency improvement at lower a slight TDP reduction versus the existing Platinum they have. Unless Amazon decides to pocket the saving, that would have a massive impact on the vCPU $ comparison.

    https://www.anandtech.com/show/15542/intel-updates...
    Reply
  • Andrei Frumusanu - Tuesday, March 10, 2020 - link

    Hyperscalers never pay full list price for their special SKUs, so comparisons to public new SKUs like the 6248R are not relevant.

    We're happy to update the landscape once EC2 introduces newer generation instances, but for now, these are the current prices and costs for what's available today and in the next few months.
    Reply
  • Spunjji - Wednesday, March 11, 2020 - link

    I'm confused. Either you can think that everything boils down to $/vCPU/hr, in which case the only thing that's relevant is what Amazon actually offer, or you can think that "a discussion around the 'new' Xeon Gold R is warranted". They're mutually exclusive. Reply
  • close - Tuesday, March 10, 2020 - link

    Great write-up Andrei. One question (I hope I didn't miss the answer in the article). Does Amazon's chip come out in front in the cost analysis because Amazon decided to take a loss or overcharge the other options, or is it an organic difference where it's intrinsically better? Reply
  • Andrei Frumusanu - Tuesday, March 10, 2020 - link

    We have no idea of Amazon's internal cost structure, so take the cost analysis from and end-user TCO perspective. Reply
  • eek2121 - Tuesday, March 10, 2020 - link

    I suspect the TDP of this chip is likely in the 150 watt range. We also know nothing about the operating environment of any of the chips. For example, the chip is rated for DDR4 3200, but is it running at 3200 speeds? The EPYC chip likely is NOT. So many questions here... Reply
  • Andrei Frumusanu - Tuesday, March 10, 2020 - link

    It is running 3200, Amazon confirmed that.

    They didn't comment on TDP, but given Arm and Ampere's figures, I think my estimate is correct.
    Reply
  • Flunk - Thursday, April 9, 2020 - link

    They're comparing VMs with the same cost/hour. What number of cores/threads is isn't really relevant. Reply
  • autarchprinceps - Sunday, October 25, 2020 - link

    That’s exactly why they reserved the entire hardware. If you run only a single workload on SMT, that single thread can use the entire core. That’s kind of the point of SMT. Reply

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