Ampere Unveils 192-Core CPU, Controversial Benchmarks

Ampere
(Image credit: Ampere)
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Ampere this week introduced its AmpereOne processors for cloud datacenters that happen to be the industry's first general-purpose CPUs with up to 132 that can be used for AI inference.

The new chips consume more power than their predecessors — Ampere Altra (which will remain in Ampere's stable for at least a while) — but the company claims that despite of higher power consumption, its processors with up to 192 cores provide higher computational density than CPUs from AMD and Intel. Some of those performance claims can be controversial.

Anton Shilov
Contributing Writer

Anton Shilov is a contributing writer at Tom’s Hardware. Over the past couple of decades, he has covered everything from CPUs and GPUs to supercomputers and from modern process technologies and latest fab tools to high-tech industry trends.

  • Amdlova
    Somenthing really wrong with these claims.

    If look for power every single chasis of ampere will give 3360 cores from epyc. Stupid math but epyc cpu can handle more than one vm per core. Some one has some knowledge over how vm works on these machines.
    Reply
  • Findecanor
    > ... interconnected using a mech network ...

    That would be so cool!
    Reply
  • OriginFree
    Findecanor said:
    > ... interconnected using a mech network ...

    That would be so cool!

    So much better than Intel's Gundam network.
    Reply
  • And it would use all the MechWarrior sounds

    “ internal ammo explosion detected”
    Reply
  • gravitate
    Lol I'm sorry but Ampere can't be taken serious. The article mentions availability, well, I hate to break it to everyone, but enterprise processor manufacturing/allocations are made years in advance and are a binning game with whether or not Ampere will even actually achieve 3 Ghz. When companies actually run workloads on machines running Intel, AMD, Ampere or Graviton, the reality is that real-world workloads don't see a real benefit from hosts running things like Ampere.

    Graviton is the single best performing host for compute and can actually scale.

    Price per performance $ is what actually matters. Plus, companies like Microsoft that use Ampere still need 20% of their compute to even run hypervisor.
    Reply
  • bit_user
    I'm not one to complain much about this, but the article starts off with several basic editing errors that are hard to miss.

    From the very first sentence:
    ... the industry's first general-purpose CPUs with up to 132 that can be used for AI inference.
    Should read:
    "... the industry's first general-purpose CPUs with up to 192 cores that can be used for AI inference."
    Third paragraph:
    interconnected using a mech network
    mesh network, obviously.

    Fourth paragraph:
    The company claims that its new cores are further optimized for cloud and AI workloads and feature 'power and are efficient' instructions per clock (IPC) gains

    Should be 'power- and area- efficient'.


    Moving on to the benchmarks, the VMs/rack calculation is weird. Not only because they're using single-CPU machines, but also because they're not accounting for SMT with Intel or AMD. Even when I compute it their way, I get 2496 cores per rack, not 2688. But, if you look at vCPUs with SMT enabled, then Genoa gets 4992.

    And if those are having to tackle workloads like AI, they're going to perform a lot better than cores with a mere dual 128-bit SIMD.

    My last point about that VMs/rack analysis: just how common are single-vCPU VMs, anyway?


    Considering AI performance, the end-notes are quite telling:
    AMD tested with 256 GB mem; AmpereOne had 512 GB.
    AMD tested with kernel 5.18.11; AmpereOne had 6.1.10.
    AMD tested with fp32; AmpereOne used fp16
    I'm also left to wonder whether AVX-512 was even used, on AMD. It won't have been enabled by -march=native, in the GCC version included with Ubuntu 22.04, because GCC didn't have patches for Genoa yet. And if they had used AVX-512, then they should've tested using BF16, which Zen 4 does support.

    If they'd tested AMD with the same kernel, 384 GB or 768 GB of RAM (so, 12-channel mode, as the article pointed out wasn't used), and BF16 via AVX-512, then I think it'd have easily equaled, if not actually trounced Ampere. Where Ampere might still pull out a win is on AI perf/W. That'd at least be something.
    Reply