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
POST A COMMENT

95 Comments

View All Comments

  • notladca - Tuesday, March 10, 2020 - link

    I would love to know if the product line has split within Annapurna. In other words whether Graviton2 has, like previous Annapurna SoCs, some interesting support around storage and networking for use in future Nitro. It's possible Amazon has some behind the scenes work going on with CCIX for future machines. For example integrating their Inferentia chip more closely with the SoC.

    Given the core count, it'd also be interesting to compare ML inference acceleration via fp16 and int8 dot product instructions per core vs use of GPU or Inferentia.
    Reply
  • coder543 - Tuesday, March 10, 2020 - link

    One small bit of feedback: with that CPU topology chart, the coloration seems a little off. A difference of +/- 1 yields very different shades of red and orange, but the same difference on the green side of the spectrum yields no discernible difference in color? Personally, I think all of the 200 +/- 5 values in the first topology chart should be an almost uniform sea of orange/red. The important thing is the 150 difference in latency, not the +/- 1 latency, and the noise in the colors distracts the reader from the primary distinction. A lower signal to noise ratio.

    Also: what is the unit? nanoseconds? microseconds? milliseconds? I can’t figure it out, and it’s not labeled as far as I can tell.
    Reply
  • Andrei Frumusanu - Tuesday, March 10, 2020 - link

    Nanoseconds, I'll add a remark. Reply
  • sing_electric - Tuesday, March 10, 2020 - link

    My tin hat is telling me to be suspicious of Amazon's pricing here. When shopping for cloud computing, perf/$ becomes VERY alluring, but I have to wonder if Amazon is willing to let its Gravitron servers be a "loss leader," artificially lowering prices to get market share until Arm on server is well-established - before then raising prices to something closer to a economically sustainable number. Reply
  • Andrei Frumusanu - Tuesday, March 10, 2020 - link

    Vertical integration is powerful. Amazon can share profits and margins division wide, not having to pay overhead to AMD/Intel. Reply
  • sing_electric - Tuesday, March 10, 2020 - link

    True, but then Amazon has to pay for the ARM license and 100% of the development/production costs. I would be very surprised if they managed to *make money* on the 1st couple Graviton generations (especially if you factor in having to buy Annapurna), since you'd need to say "of the $X generated by Graviton metal, $Y would have been spent on EC2 anyways, meaning $Z is our actual gain," and that's... probably too much to ask at this stage. Reply
  • rahvin - Tuesday, March 10, 2020 - link

    The costs you mention are nothing compared to what they pay right now with Intel or AMD with they 50% margins on top of the actual cost. IMO this initiative was born out of Intel's price increases from 2010 to now. By vertically integrating they have full control over the price structure and they have very good data on what kind of workloads are running so they can tailor the design.

    IMO it was just a question of time until Amazon tried to vertically integrate this like they've done with shipping and lots of other stuff. Bezos is following the Robber Barron growth model.
    Reply
  • dotjaz - Wednesday, March 11, 2020 - link

    Huh? AMD has a gross margin of 40%, true. But keep in mind AWS has a operating margin of 30%, that mean AWS has a even higher gross margin than AMD, comparable to AMD's server department.
    Do you know what that means? For $1 of expenditure in to chip manufacturing, AWS expects to earn as much as AMD does. And since AWS don't have the volume as far as chip goes, their gross margin for chip investment will be lower, therefore not worth the investment if the decision is purely financial.

    But yes, the other point stands, AWS have better control of costing (with more leverage as well) and performance.
    Reply
  • Wilco1 - Wednesday, March 11, 2020 - link

    For every $1 worth of silicon you could pay AMD $1.50, pay Intel $2 or pay TSMC $1 plus $0.20 internal development costs. Which works out best you think? Reply
  • extide - Friday, March 13, 2020 - link

    It's not that simple. AMD and Intel can spread those development costs over vastly more processors. I mean we'll never know how it truly breaks down -- but I'd imagine Amazon has figure this all out and this will be pretty profitable for them. Reply

Log in

Don't have an account? Sign up now