NVIDIA's Carmel CPU Core - SPEC2006 Speed

While the Xavier’s vision and machine processing capabilities are definitely interesting, it’s use-cases will be largely out-of-scope for the average AnandTech reader. One of the aspects of the chip that I was personally more interested in was NVIDIA’s newest generation Carmel CPU cores, as it represents one of the rare custom Arm CPU efforts in the industry.

Memory Latency

Before going into the SPEC2006 results, I wanted to see how NVIDIA’s memory subsystem compares against some comparable platform in the Arm space.

In the first logarithmic latency graph, we see the exaggerated latency curves which make it easy to determine the various cache hierarchy levels of the systems. As NVIDIA advertises, we see the 64KB L1D cache of the Carmel cores. What is interesting here is that NVIDIA is able to achieve quite a high performance L1 implementation with just under 1ns access times, representing a 2-cycle access which is quite uncommon. The second hierarchy cache is the L2 that continues on to the 2MB depth, after which we see the 4MB L3 cache. The L3 cache here looks to be of a non-uniform-access design as its latency steadily rises the further we go.

Switching back to a linear graph, NVIDIA does have a latency advantage over Arm’s Cortex-A76 and the DSU L3 of the Kirin 980, however it loses out at deeper test depths and latencies at the memory controller level. The Xavier SoC comes with 8x 32bit (256bit total) LPDDR4X memory controller channels, representing a peak bandwidth of 137GB/s, significantly higher than the 64 or 128bit interfaces on the Kirin 980 or the Apple A12X. Apple overall still has an enormous memory latency advantage over the competition as its massive 8MB L2 cache as well as the 8MB SLC (System level cache) allows for significant lower latencies across all test depths.

SPEC2006 Speed Results

A rarity for whenever we're looking at Arm SoCs and products built around them, NVIDIA’s Jetson AGX comes with a custom image for Ubuntu Linux (18.04 LTS). On one hand, including a Linux OS gives us a lot of flexibility in terms of test platform tools; but on the other hand, it also shows the relatively immaturity of Arm on Linux. One of the more regretful aspects of Arm on Linux is browser performance; to date the available browsers are still lacking optimised Javascript JIT engines, resulting in performance that is far worse than any commodity mobile device.

While we can’t really test our usual web workloads, we do have the flexibility of Linux to just simply compile whatever we want. In this case we’re continuing our use of SPEC2006 as we have a relatively established set of figures on all relevant competing ARMv8 cores.

To best mimic the setup of the iOS and Android harnesses, we chose the Clang 8.0.0 compiler. To keep things simple, we didn’t use any special flags other than –Ofast and a scheduling model targeting the Cortex-A53 (It performed overall better than no model or A57 targets). We also have to remind readers that SPEC2006 has been retired in favour of SPEC2017, and that the results published here are not officially submitted scores, rather internal figures that we have to describe as estimates.

The power efficiency figures presented for the AGX, much like all other mobile platforms, represent the active workload power usage of the system. This means we’re measuring the total system power under a workload, and subtracting the idle power of the system under similar circumstances. The Jetson AGX has a relatively high idle power consumption of 8.92W in this scenario, much that can be simply be attributed from a relatively non-power optimised board as well as the fact that we’re actively outputting via HDMI while having the board connected to GbE.

In the integer workloads, the Carmel CPU cores' performance is quite average. Overall, the performance across most workloads is extremely similar to that of Arm’s Cortex-A75 inside the Snapdragon 845, with the only outlier being 462.libquantum which showcases larger gains due to Xavier’s increased memory bandwidth.

In terms of power and efficiency, the NVIDIA Carmel cores again aren’t quite the best. The fact that the Xavier module is targeted at a totally different industry means that its power delivery possibly isn’t quite as power optimised as on a mobile device. We also must not forget that the Xavier has an inherent technical disadvantage of being manufactured on a 12FFN TSMC process node, which should be lagging behind Samsung’s 10LPP processes of the Exynos 9810 and the Snapdragon 845, and most certainly represents a major disadvantage against the newer 7nm Kirin 980 and Apple A12.

On the floating point benchmarks, Xavier fares overall better because some of the benchmarks are characterised by their sensitivity to the memory subsystem; in 433.milc this is most obvious. 470.lbm also sees the Carmel cores perform relatively well. In the other workloads however, again we see Xavier having trouble to differentiate itself much from the performance of a Cortex A75.

Here’s a wider performance comparison across SPEC2006 workloads among the most recent and important ARMv8 CPU microarchitectures:

Overall, NVIDIA’s Carmel core seems like a big step up for NVIDIA and their in-house microarchitecture. However when compared against most recent cores from the competition, we see the new core having trouble able to really distinguish itself in terms of performance. Power efficiency of the AGX also lags behind, however this is something that was to be expected given the fact that the Jetson AGX is not a power optimised platform, beyond the fact that the chip’s 12FFN manufacturing process is a generation or two behind the latest mobile chips.

The one aspect which we can’t quantize NVIDIA’s Carmel cores is its features: This is a shipping CPU with ASIL-C functional safety features that we have in our hands today. The only competition in this regard would be Arm’s new Cortex A76AE, which we won’t see in silicon for at least another year or more. When taking this into account, it could possibly make sense for NVIDIA to have gone with its in-house designs, however as Arm starts to offer more designs for this space I’m having a bit of a hard time seeing a path forward in following generations after Xavier, as competitively, the Carmel cores don’t position themselves too well.

Machine Inference Performance & What's it For? NVIDIA's Carmel CPU Core - SPEC2006 Rate
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  • syxbit - Friday, January 04, 2019 - link

    I wish Nvidia hadn't abandoned the mobile space. They could have brought some much needed competition :( :(. Reply
  • Despoiler - Friday, January 04, 2019 - link

    The only design that was competitive was the one selected by Google for one generation. 4 ARM cores + a 5th core for power management was a huge failure when everyone can do PM within the ARM SOC. It was only cost competitive in other words. Reply
  • syxbit - Friday, January 04, 2019 - link

    The Tegra X1 was a great chip when released.
    The Shield TV still uses it, and it's an excellent (though now old) chip.
    Reply
  • Alistair - Friday, January 04, 2019 - link

    And that's not a mobile device. Perf/W for Xavier is also really poor vs. the newest Huawei silicon also. Reply
  • BenSkywalker - Friday, January 04, 2019 - link

    The Switch is mobile. When the x1 debuted *four* years ago it obliterated the best from Apple, roughly 50%-100% faster on the gpu side. So yes, if we give the other soc manufacturers four years and a four process step advantage, they can edge out Tegra.

    Qualcomm's lawyers should take a bow on nVidia not being still present in the mobile market, certainly not the laughable "competition" they had on the technology side.

    "Having a hard time seeing a path forward"... That was a cringe worthy line. Why not benchmark direct x on an iPhone and then say the same about the Ax line? Let's take a deep learning/ai platform and benchmark it using antiquated pc desktop applications and then act like there are fundamental design issues... ?
    Reply
  • TheinsanegamerN - Friday, January 04, 2019 - link

    The tegra X1 doesnt run anywhere near full speed when the device is not plugged into a power source. The Switch also has a fan. It's pretty easy to "obliterate" the competition when you are using a different form factor. I mean, the core I7 with iris pro 580 GPU obliterates the tegra X1, so the X1 must not be very good right?

    The X1 was WAY too power hungry to use in anything other then a dedicated gaming device with a dedicated cooling system. When restricted down to tablet TDPs, the X1's performance drops like a lead rock.

    So, yeah, maybe with another 4 years nvidia could make the tegra work in a proper laptop. Meanwhile, Apple has ALREADY done that with the A12 SoC, and that works in a passive tablet. Nvidia was never able to make their SoC work in a similar system.
    Reply
  • Alistair - Saturday, January 05, 2019 - link

    Are you replying to my comment? Xavier is new for 2018 and so is Huawei's Kirin 980. We are talking about Xavier, not X1. And Apple's tablet GPU for 2015 equaled nVidia's in perf. The iPad Pro's A9X equalled the Tegra x1 in GPU performance while surpassing it in CPU performance, and at a lower power draw... Reply
  • Alistair - Saturday, January 05, 2019 - link

    I think you were conveniently comparing the 2014 iPad's vs. the 2015 X1, instead of the 2015 iPad Pro vs. the X1. Reply
  • Samus - Saturday, January 05, 2019 - link

    ^^this Reply
  • niva - Friday, January 04, 2019 - link

    Why are there video ads automatically playing on each one of the Anandtech pages? I know you guys are trying to monetize but you've crossed lines that make it annoying for your users to keep visiting the site. Reply

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