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hoakley March 30, 2022 Macs, Technology

The hunt for the M1's neural engine

After yesterday's explanation of the Apple Neural Engine (ANE) in M1
series Macs, it's time to go in search of this elusive part of Apple
Silicon chips, and discover how it's used.

So far, all I have seen of the ANE are some entries in the log, and
claims for how much it can accelerate Machine Learning (ML). The ANE
first makes its appearance early during the kernel phase of the boot
process, initially through its Load Balancer, which is initialised
with
virtual bool H1xANELoadBalancer::init(OSDictionary *) WE are here:
H1xANELoadBalancer: 30
H1xANELoadBalancer::probe
virtual IOService *H1xANELoadBalancer::probe(IOService *, SInt32 *)
WE are here: H1xANELoadBalancer: 51, res: <private&rt;, score: 0
H1xANELoadBalancer::start, provider: <private&rt;
H1xANELoadBalancer::start, res: 1
WE are here: H1xANELoadBalancer
virtual bool H1xANELoadBalancer::start(IOService *) :H11ANEIn::start
- ANE LB is enabled by default!

That's followed by the ANE interface:
static AppleH1xANEMsgQue
*AppleH1xANEMsgQue::WithLoadBalancerInterface(H1xANELoadBalancer *)
static AppleH1xANEMsgQue
*AppleH1xANEMsgQue::WithLoadBalancerInterface(H1xANELoadBalancer *)
line 37
IOReturn AppleH1xANEMsgQue::startMsgQ(H1xANELoadBalancer *)
static AppleH1xANEMsgQue
*AppleH1xANEMsgQue::WithLoadBalancerInterface(H1xANELoadBalancer *)
Done
then the Load Balancer again
H1xEventSource::initWithOptions
H1xEventSource::enable
Done H1xANELoadBalancer, start H1xANEMessages workloop
followed later by other messages recording initialisation of the ANE
interface.

After that, ANE seems to get along with its work quietly. During
Visual Look Up, mediaanalysisd is a bit more forthcoming, posting
short sequences at the start of each run of the ANE like
Found matching service: H1xANELoadBalancer
Found ANE H1xANELoadBalancer :1
Found matching service: H11ANEIn
Found ANE device :2
Total num of devices 2
LB Found at index 0
(Single-ANE System with LB) Opening H11ANE device
H11ANEDevice::H11ANEDeviceOpen, usage type: 1
H11ANE Device Open succeeded with usage type: 1
(Single-ANE System with LB) Selected H11ANE device

Those are followed by a series of messages written by
com.apple.Espresso, which manages the ANE during Visual Look Up.

I next looked for an app which might load the ANE. Geekbench ML
looked promising, but so far only seems available for iOS and
Android, so I built my own using one of Apple's ML demo projects.
That ran consistently faster on M1 series Macs than on this Intel
iMac Pro. For instance, the median time to complete one learn and
test cycle was 2.26 seconds on Intel, and 1.21 seconds on M1 Macs.
That's a similar magnitude of acceleration that I have seen during
neural network sections of Visual Look Up.

The acid test, though, was inspecting the responses of the ANE using
powermetrics. That's something of a monster, which can dump fine
detail about each core and a great deal more, including a little
about the ANE. Once running my test ML app, it was soon taking 100%
active residency on the first of the P cores at a frequency of
3036-3228 MHz. However, that app didn't make the ANE or GPU blink:
ANE power remained steadfastly at 0 mW, with GPU power at only 5 mW
and idling at 4 MHz. That's in spite of the app making plenty of
calls to use BNNS, and running for several seconds.

It was therefore time to return to the one feature which I know
reliably invokes the ANE repeatedly, Visual Look Up (VLU). Running a
series of powermetrics samples during successful VLU finally
demonstrated the salience of the ANE.

In the first sampling period of a second, ANE drew 30 mW power,
dropping slightly to 22 mW in the second period, then peaking at 49
mW in the third. ANE read reached a maximum of 232 MB/s and write 167
MB/s. GPU power and frequency remained low, suggesting that the ML
code in VLU is normally handled by the ANE. Those figures correspond
to the first phase of VLU involving analysis and parsing. The second,
of visual search, was accompanied by shorter and lower ANE activity.

Conclusions

  * Visual Look Up on M1 series Macs consistently uses the Apple
    Neural Engine.
  * VLU's call chain is through mediaanalysisd, which uses Espresso
    to manage the ANE. Espresso is also used on Intel Macs to manage
    neural networks run on their CPU cores.
  * Maximum power drawn by the ANE was 49 mW, which is low even in
    comparison to that required by E cores.
  * The ANE reached high peak (memory) read and write rates of 232
    and 167 MB/s during use.
  * BNNS functions may be run entirely on CPU cores, even when they
    appear suitable for the ANE, and the ANE is available.
  * powermetrics is the tool of choice for observing ANE activity;
    indeed, it appears to be the only tool.

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Posted in Macs, Technology and tagged ANE, Apple Neural Engine, BNNS,
Espresso, M1, ML, power, powermetrics, Visual Look Up. Bookmark the
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3Comments

Add yours

 1. 1 [1e8647b69e37]
    RobinDumontChaponet on March 30, 2022 at 9:53 pm
    Reply

    Hi. Doesn't Final Cut Pro X video analysis use the ANE ? (Like
    the subject centering auto framing)

    LikeLiked by 1 person

      + 2 [6986a746f627]
        hoakley on March 30, 2022 at 10:01 pm
        Reply

        I'm sorry, I don't know. It should be straightforward to find
        out using powermetrics.
        Howard.

        LikeLike

          o 3 [1e8647b69e37]
            RobinDumontChaponet on March 30, 2022 at 10:17 pm
            Reply

            No problem. Simple curiosity over which programs can
            access it. ...I don't even own an M1 machine.

            (I do own an eGPU that since macOS 12 I cannot eject
            without an alert mentioning that medianalysisd is still
            using the GPU. But that is another although somewhat
            related subject.)

            Thank you for your response.

            LikeLiked by 1 person

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In memoriam Piero di Cosimo, who died 500 years ago, 1
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