Cost Analysis - An x86 Massacre

The Graviton2 showcased that it can keep up extremely well in terms of performance and throughput, even beating the competition in a lot of the tests. However sometimes you don’t care too much about performance, and you just want to get some workload completed in the cheapest way possible, at which point value comes into play.

Amazon does allude to that, stating that the new chip is able to achieve 40% better performance per dollar than its competition. As covered in the introduction, for the 64-vCPU count 16xlarge instances the m6g (Graviton2), m5a (EPYC1), and m5n (Xeon Cascade Lake) are priced at an hourly cost of $2.464, $2.752 and $3.808 respectively.

Translating the time to completion of our various SPEC tests to hours and multiplying by the hourly cost, we end up with a cost per fixed workload metric:

An aggregate of all workloads summed up together, which should hopefully end up in a representative figure for a wide variety of real-world use-cases, we do end up seeing the Graviton2 coming in 40% cheaper than the competing platforms, an outstanding figure.

If we were to compare the same fixed workload at smaller instance counts, because of Graviton2’s better per-thread performance, we’re seeing even better results on 4xlarge (16 vCPUs) instances. Here the Amazon chip showcases 43% better value than the Xeon chip, and beats the AMD instances by being 53% cheaper.

If we were to transform the results into a fixed throughput per dollar metric, we again see the Graviton2 far ahead. The unit here is SPEC runs per dollar.

The lower the vCPU instance size, the better value the Graviton2 seemingly becomes, as its performance with increased vCPUs scales sublinearly, but the cost of bigger vCPU instances scales linearly, an effect that’s almost not present at all in the AMD system, and only marginally present in the Xeon instances.

Again, the Graviton2’s scaling here might differ in production instances, but given that you can’t just chop off half the chip (or have access to only one of two sockets, in Intel’s case here) and that Amazon seemingly isn’t doing any static partitioning of the chip’s shared resources, I do think it’s more likely than not that such performance and value figures will be encountered in the real-world.

Even ignoring the lower vCPU instances, Amazon was able to deliver on its promise of 40% better performance per dollar, and it’s a massive shakeup for the AWS and EC2 ecosystem.

SPEC - MT Performance (4xlarge 16 vCPU) Conclusion & End Remarks
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  • anonomouse - Wednesday, March 11, 2020 - link

    Have you looked at the benchmarks in GCP PerfKitBenchmarker (https://github.com/GoogleCloudPlatform/PerfKitBenc... It includes benchmark versions of various popular benchmarks including variants of ycsb on different databases, oltp, cloudsuite, hadoop, and a bunch of wrapper infrastructure around running the tests on cloud providers. Reply
  • anonomouse - Wednesday, March 11, 2020 - link

    Okay so maybe the comment system doesn't have well with links:

    https://github.com/GoogleCloudPlatform/PerfKitBenc...
    http://googlecloudplatform.github.io/PerfKitBenchm...
    Reply
  • yeeeeman - Tuesday, March 10, 2020 - link

    Ok, now imagine this chip with apple custom cores. Even Zen wouldn't stand a chance. Reply
  • HStewart - Tuesday, March 10, 2020 - link

    You can't truly say that. Keep in mind both Apple and Amazon are aim at there own custom environments - things are like different in real world. Reply
  • Duncan Macdonald - Tuesday, March 10, 2020 - link

    The Apple CPU cores are larger and more power hungry when loaded hard than the CPU cores on the N1. A 64 CPU chip with the high performance cores from the Apple A13 would consume far more power than the N1 and would be quite a bit larger than the N1. The Apple A13 chip (in the iPhone 11) is suited for intermittent load not the sustained use that server type chips such as the N1 have to deal with. Reply
  • arashi - Wednesday, March 11, 2020 - link

    Yikesman Reply
  • edsib1 - Tuesday, March 10, 2020 - link

    You are using an Epyc processor that is nearly 3 years old.

    Surely you should use this years model (or a 64-corer threadripper if you dont have one)
    Reply
  • vanilla_gorilla - Wednesday, March 11, 2020 - link

    You should consider reading the article and then you would know exactly why they are using those CPU. Reply
  • Kamen Rider Blade - Tuesday, March 10, 2020 - link

    The benchmarks feel incomplete. Why don't you have a 64-core Zen2 based processor in it to compare?

    Even the ThreadRipper 64-core would be something.

    But not having AMD's latest Server grade CPU in your benchmarks really feels like you're doing a disservice to your readers, especially since we've seen your previous reviews with the Zen 2 64 core monster.
    Reply
  • Rudde - Wednesday, March 11, 2020 - link

    Read the article! Rome is mentioned over five times. In short, Amazon doesn't offer Rome instances yet and Anandtech will update this article once they do. Reply

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