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I'm still trying to find a way to monitor the Neural Engine on my Macbook air M1, but the APIs are non-existent, there's barely anything in the docs and no answ

I'm still trying to find a way to monitor the Neural Engine on my Macbook air M1, but the APIs are non-existent, there's barely anything in the docs and no answer from Apple. My models train fast, 3x faster than most i7 computers with GPU, which is excellent for a fanless ultraportable computer but I wish Apple would treat the NE as a 1st class citizen on these machines, with Mac SDK APIs and usage visualization in the Activity Monitor.

okamiueru 5y ago
> 3x faster than most i7 computers with GPU Can you back that statement up with anything, or at least clarify it? You seem to suggesting a non-mac i7 with a separate GPU. Also, just an FYI, "i7" says pretty much nothing. The i7s have existed since 2009. I don't know. The statement is just so vague and ridiculous. The M1 is probably the worst hardware you could have picked in 2020-2021 if computational power was your main concern. For highly parallelizable work tasks, the top end GPU alone has 10x the computation power than the M1, and a top end CPU has around 4x the computation power than the M1. Not to mention a rather limiting 16GB of memory. That the M1 is computationally powerful is a myth started out by exceedingly misleading marketing and reinforced with hard-to-compare benchmarks. To possibly save someone the trouble, the responses to a comment such as this, from experience will be: 1. "power consumption is much much better on M1 than anything else." True, but, then again, your use case must then prioritize power consumption, and not computation power. So which is it? The use case for a compute cluster on a train is rather contrived. 2. "When apple scales up the M1 to more cores, they will magically be able to retain all the benefits possible with a low core count, and scale it up without any problems or compromises, just you wait.". Ok, I'll wait. 3. "It's not fair to compare a laptop with a desktop". Of course it is. The constraints for comparison are already stated: computation power being the main priority. If someone buys hardware to do heavy computations, you can pick and chose depending on your needs. If you need it to be a laptop, or you need it to draw little power, then I'm sure you can factor this in accordingly.
- jonathanstrange 5y ago
  I don't know about the M1, to be honest, but I used to be an Apple customer and ardent fanboy (so embarrassing!) during the golden PPC age and remember very well Apple's inflated claims about performance, which all turned out to be false the minute they switched to Intel. So I agree with your comment, it's advisable to always take miraculous performance claims with a grain of salt.
  - rjmunro 5y ago
    Were the performance claims false, or did Intel just catch up, while PowerPC stagnated?
    - jonathanstrange 5y ago
      They were misleading to false, depending on how you interpret it. The claims were true for certain specialized microbenchmarks and false in general. PPC programs running tasks that could be optimized for using Altivec instructions could be much faster than on comparable Intel chips, but those tasks were rare and normal programs were slower than on Intel. Apple themselves changed their tune about the difference almost overnight.
  - machello13 5y ago
    Surely, with the M1s having been actually publicly available for many months now, there's enough data and benchmarks out there that we don't need to take Apple's performance claims with any salt?
- whynotminot 5y ago
  > That the M1 is computationally powerful is a myth started out by exceedingly misleading marketing and reinforced with hard-to-compare benchmarks It feels like you've constructed quite the straw-man to tear down. Praise for the M1 is in the context of the form factors it exists in and the efficiency it works at. Of course you can find more powerful hardware in larger form factors drawing 10x the power from the mains. The M1 runs in an iPad for crying out loud. > The constraints for comparison are already stated: computation power being the main priority. Then don't buy a bloody M1. The M1 has always been Apple's entry-level efficiency-first processor. We haven't even seen the "Pro" stuff yet.
  - smoldesu 5y ago
    He's not wrong though. I own an M1 Macbook Air, and while there are some workloads that it can outperform my desktop at, it's still not even close to the level of functionality or comparability of my other machines. Hell, most days I just end up tossing my Thinkpad in my work bag, just because the keyboard and OS gets in my way less. > Then don't buy a bloody M1. The M1 has always been Apple's entry-level efficiency-first processor. No, I gotta disagree. Apple's marketing around the M1 was intentionally deceptive: they were forced to revoke their claim of having the "fastest CPU cores" after it was vehemently disproven. Their "faster than 97% of Windows laptops" conveniently didn't compare itself to AMD laptops or laptops with dedicated graphics. I'm just not really impressed. I seriously worry for Apple if this is all they were able to get out of the 5nm node on ARM. Considering how poorly ARM scales with higher TDPs, I don't think I want to see their "Pro stuff".
    - whynotminot 5y ago
      > He's not wrong though. I own an M1 Macbook Air, and while there are some workloads that it can outperform my desktop at My point is that this isn't even an interesting conversation to have. Your desktop can outperform a chip that runs an iPad? Cool story bro. > they were forced to revoke their claim of having the "fastest CPU cores" after it was vehemently disproven. Their announcement explicitly said "when it comes to low power silicon." So many of you insisted on missing this part it's practically a meme now. Watch the accouncement video here: https://www.youtube.com/watch?v=5AwdkGKmZ0I https://www.youtube.com/watch?v=5AwdkGKmZ0I and scrub to 8:45 and actually listen to what is said. > laptops with dedicated graphics Why should they be forced to compare their integrated graphics to laptops with dedicated graphics? This is yet another uninteresting comparison. Of course a machine with some dedicated mobile 3080 is going to win the day in a head to head. But it's an absurd comparison because said machine will draw vastly more power and be heavier to boot. It's a different category of machine at that point. > I seriously worry for Apple if this is all they were able to get out of the 5nm node on ARM I think you're the only one who's worried. Apple very clearly laid out their design goals with the M1: supremacy at performance per watt. And the fanboys protested with "I can build a faster desktop" or "my 4.5 lb laptop with dedicated graphics can get more FPS." It's just baffling. You've missed the whole point.
- jolux 5y ago
  If you thought a MacBook Air was going to replace a purpose-built machine learning workstation of course buying it would be a mistake, because it won’t do that. It only supports up to 16GB of RAM! But what other computer in that form factor comes close? The argument is that the higher efficiency will translate into more powerful chips in HEDT products too. I wouldn’t take that on faith but I think they have a decent chance of pulling it off. Apple doesn’t do transitions like this is if they don’t think they can knock them out of the park. There have been rumors about them switching the Mac to ARM for nearly 10 years at this point.
  - smoldesu 5y ago
    > But what other computer in that form factor comes close? Basically all of them, as long as you aren't training your models on your CPU like it's 2011.
    - jolux 5y ago
      Which other ultrabooks, specifically? It’s definitely not all of them, if you’ve been reading the benchmarks.
- YetAnotherNick 5y ago
  > The constraints for comparison are already stated: computation power being the main priority Who compares ultrabook to desktop for the multithreaded computation power? Assume you only want that without any regards to power or space or cost, by your logic you could buy 1000 mac mini and the computational power will be more than any desktop computer.
  - okamiueru 5y ago
    See 3.
- ribit 5y ago
  > The M1 is probably the worst hardware you could have picked in 2020-2021 if computational power was your main concern. For highly > parallelizable work tasks, the top end GPU alone has 10x the computation power than the M1, and a top end CPU has around 4x the > computation power than the M1. Not to mention a rather limiting 16GB of memory. This statement is so banal that I am not sure how to comment on it. I never understood the logic of people who point out that an entry-level, low power chip targeted at ultraportable laptops and kitchen computers cannot compete with high-end desktops. It's just as ridiculous as to complain that AMD EPYC is too big to fit into a laptop. M1 is obviously a terrible choice if you are looking for a deskbound HPC workstation. It's a terrific choice if you are looking for an ultraportable laptop with excellent battery life that you would still like to prototype your ML code on before running the full workload on a mainframe. > That the M1 is computationally powerful is a myth started out by exceedingly misleading marketing and reinforced with hard-to- > compare benchmarks. More like a myth perpetuated by people who like to take facts out of the context. In terms of the underlaying IP, M1 is terrific technology. It can deliver the same performance as state of the art designs at a fraction of the power consumption. In terms of absolute performance, it's obviously an entry-level chip, and it performs exceedingly well compared to other offerings in this segment. And even outside its segment it is no slouch either. It runs my database scripts and builds code faster than my Intel i9 laptop, despite using 70% less power and half as many performance-oriented CPU cores.
  - okamiueru 5y ago
    > This statement is so banal that I am not sure how to comment on it. ... > M1 is obviously a terrible choice if you are looking for a deskbound HPC workstation ... So, in one breath you say my statement is banal, in the next you agree with it. The thing I take issue with is having to deal with the misconception that it is a replacement for a HPC workstation, because many (not you obviously) think it actually is a powerhouse. You go on to repeat the stuff about power performance, which I've already listed, and you could have spared yourself the trouble.
- ojosilva 5y ago
  I meant to write most i7 machines with a GPU where I trained my models. My post was about the lack of adequate SDKs for the NE on the M1. I don't know why the fuck you grabbed that tiny fraction and just ran off with it like I was writing an appleboy marketing manifesto on the M1 prowess.
  - okamiueru 5y ago
    I mean... you are doing what I find more than a few always seem to do on threads discussing the M1. Which is to subtly suggest that it is a computational powerhouse, with vague and non-verifiable metrics (your post that I originally replied to is a good example). Agreeing to disagree should be possible, and the request you got for a follow up to give some more specific details was polite, and should not have been that hard to deal with. It was also genuinely interested in an answer, so I question the appropriateness of the langue your responded with. And, I might also remind you that as far as answering the question, it did not. If you haven't already, I'd suggest looking at https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html. And I mean that too in a polite way, as it is easy to get carried away and assume the worst in anonymous conversations with strangers. So, to summarize. Apple originally made highly misleading statements on the computational power of the M1, and since then, this misconception is repeated quite often. After a while, it gets annoying to see new posts on HN, week after week. Now, alluding that an M1 is 3x faster at training models than discrete GPUs can only be true if it is a decade old hardware. And as that stands, your original comment was asked to be clarified. After all, it's not unheard of for M1 benchmarks to disable the discrete GPU of the PC it is compared to, for "fairness". Limiting the training to a single CPU core for "even more fairness" would be par for the course. So, I did not suggest you were an "appleboy", as you put it. I asked what kind of hardware you actually experienced a 3x speedup on, as the i7 goes back to 2009, and "GPU", well, further back. In any case, and this might come as a surprise, feel free to not answer. But, then, I can only wish that you refrain from making the effort at a rude response.

okamiueru 5y ago

> 3x faster than most i7 computers with GPU Can you back that statement up with anything, or at least clarify it? You seem to suggesting a non-mac i7 with a separate GPU. Also, just an FYI, "i7" says pretty much nothing. The i7s have existed since 2009. I don't know. The statement is just so vague and ridiculous. The M1 is probably the worst hardware you could have picked in 2020-2021 if computational power was your main concern. For highly parallelizable work tasks, the top end GPU alone has 10x the computation power than the M1, and a top end CPU has around 4x the computation power than the M1. Not to mention a rather limiting 16GB of memory. That the M1 is computationally powerful is a myth started out by exceedingly misleading marketing and reinforced with hard-to-compare benchmarks. To possibly save someone the trouble, the responses to a comment such as this, from experience will be: 1. "power consumption is much much better on M1 than anything else." True, but, then again, your use case must then prioritize power consumption, and not computation power. So which is it? The use case for a compute cluster on a train is rather contrived. 2. "When apple scales up the M1 to more cores, they will magically be able to retain all the benefits possible with a low core count, and scale it up without any problems or compromises, just you wait.". Ok, I'll wait. 3. "It's not fair to compare a laptop with a desktop". Of course it is. The constraints for comparison are already stated: computation power being the main priority. If someone buys hardware to do heavy computations, you can pick and chose depending on your needs. If you need it to be a laptop, or you need it to draw little power, then I'm sure you can factor this in accordingly.

jonathanstrange 5y ago
I don't know about the M1, to be honest, but I used to be an Apple customer and ardent fanboy (so embarrassing!) during the golden PPC age and remember very well Apple's inflated claims about performance, which all turned out to be false the minute they switched to Intel. So I agree with your comment, it's advisable to always take miraculous performance claims with a grain of salt.
- rjmunro 5y ago
  Were the performance claims false, or did Intel just catch up, while PowerPC stagnated?
  - jonathanstrange 5y ago
    They were misleading to false, depending on how you interpret it. The claims were true for certain specialized microbenchmarks and false in general. PPC programs running tasks that could be optimized for using Altivec instructions could be much faster than on comparable Intel chips, but those tasks were rare and normal programs were slower than on Intel. Apple themselves changed their tune about the difference almost overnight.
- machello13 5y ago
  Surely, with the M1s having been actually publicly available for many months now, there's enough data and benchmarks out there that we don't need to take Apple's performance claims with any salt?
whynotminot 5y ago
> That the M1 is computationally powerful is a myth started out by exceedingly misleading marketing and reinforced with hard-to-compare benchmarks It feels like you've constructed quite the straw-man to tear down. Praise for the M1 is in the context of the form factors it exists in and the efficiency it works at. Of course you can find more powerful hardware in larger form factors drawing 10x the power from the mains. The M1 runs in an iPad for crying out loud. > The constraints for comparison are already stated: computation power being the main priority. Then don't buy a bloody M1. The M1 has always been Apple's entry-level efficiency-first processor. We haven't even seen the "Pro" stuff yet.
- smoldesu 5y ago
  He's not wrong though. I own an M1 Macbook Air, and while there are some workloads that it can outperform my desktop at, it's still not even close to the level of functionality or comparability of my other machines. Hell, most days I just end up tossing my Thinkpad in my work bag, just because the keyboard and OS gets in my way less. > Then don't buy a bloody M1. The M1 has always been Apple's entry-level efficiency-first processor. No, I gotta disagree. Apple's marketing around the M1 was intentionally deceptive: they were forced to revoke their claim of having the "fastest CPU cores" after it was vehemently disproven. Their "faster than 97% of Windows laptops" conveniently didn't compare itself to AMD laptops or laptops with dedicated graphics. I'm just not really impressed. I seriously worry for Apple if this is all they were able to get out of the 5nm node on ARM. Considering how poorly ARM scales with higher TDPs, I don't think I want to see their "Pro stuff".
  - whynotminot 5y ago
    > He's not wrong though. I own an M1 Macbook Air, and while there are some workloads that it can outperform my desktop at My point is that this isn't even an interesting conversation to have. Your desktop can outperform a chip that runs an iPad? Cool story bro. > they were forced to revoke their claim of having the "fastest CPU cores" after it was vehemently disproven. Their announcement explicitly said "when it comes to low power silicon." So many of you insisted on missing this part it's practically a meme now. Watch the accouncement video here: https://www.youtube.com/watch?v=5AwdkGKmZ0I https://www.youtube.com/watch?v=5AwdkGKmZ0I and scrub to 8:45 and actually listen to what is said. > laptops with dedicated graphics Why should they be forced to compare their integrated graphics to laptops with dedicated graphics? This is yet another uninteresting comparison. Of course a machine with some dedicated mobile 3080 is going to win the day in a head to head. But it's an absurd comparison because said machine will draw vastly more power and be heavier to boot. It's a different category of machine at that point. > I seriously worry for Apple if this is all they were able to get out of the 5nm node on ARM I think you're the only one who's worried. Apple very clearly laid out their design goals with the M1: supremacy at performance per watt. And the fanboys protested with "I can build a faster desktop" or "my 4.5 lb laptop with dedicated graphics can get more FPS." It's just baffling. You've missed the whole point.
jolux 5y ago
If you thought a MacBook Air was going to replace a purpose-built machine learning workstation of course buying it would be a mistake, because it won’t do that. It only supports up to 16GB of RAM! But what other computer in that form factor comes close? The argument is that the higher efficiency will translate into more powerful chips in HEDT products too. I wouldn’t take that on faith but I think they have a decent chance of pulling it off. Apple doesn’t do transitions like this is if they don’t think they can knock them out of the park. There have been rumors about them switching the Mac to ARM for nearly 10 years at this point.
- smoldesu 5y ago
  > But what other computer in that form factor comes close? Basically all of them, as long as you aren't training your models on your CPU like it's 2011.
  - jolux 5y ago
    Which other ultrabooks, specifically? It’s definitely not all of them, if you’ve been reading the benchmarks.
YetAnotherNick 5y ago
> The constraints for comparison are already stated: computation power being the main priority Who compares ultrabook to desktop for the multithreaded computation power? Assume you only want that without any regards to power or space or cost, by your logic you could buy 1000 mac mini and the computational power will be more than any desktop computer.
- okamiueru 5y ago
  See 3.
ribit 5y ago
> The M1 is probably the worst hardware you could have picked in 2020-2021 if computational power was your main concern. For highly > parallelizable work tasks, the top end GPU alone has 10x the computation power than the M1, and a top end CPU has around 4x the > computation power than the M1. Not to mention a rather limiting 16GB of memory. This statement is so banal that I am not sure how to comment on it. I never understood the logic of people who point out that an entry-level, low power chip targeted at ultraportable laptops and kitchen computers cannot compete with high-end desktops. It's just as ridiculous as to complain that AMD EPYC is too big to fit into a laptop. M1 is obviously a terrible choice if you are looking for a deskbound HPC workstation. It's a terrific choice if you are looking for an ultraportable laptop with excellent battery life that you would still like to prototype your ML code on before running the full workload on a mainframe. > That the M1 is computationally powerful is a myth started out by exceedingly misleading marketing and reinforced with hard-to- > compare benchmarks. More like a myth perpetuated by people who like to take facts out of the context. In terms of the underlaying IP, M1 is terrific technology. It can deliver the same performance as state of the art designs at a fraction of the power consumption. In terms of absolute performance, it's obviously an entry-level chip, and it performs exceedingly well compared to other offerings in this segment. And even outside its segment it is no slouch either. It runs my database scripts and builds code faster than my Intel i9 laptop, despite using 70% less power and half as many performance-oriented CPU cores.
- okamiueru 5y ago
  > This statement is so banal that I am not sure how to comment on it. ... > M1 is obviously a terrible choice if you are looking for a deskbound HPC workstation ... So, in one breath you say my statement is banal, in the next you agree with it. The thing I take issue with is having to deal with the misconception that it is a replacement for a HPC workstation, because many (not you obviously) think it actually is a powerhouse. You go on to repeat the stuff about power performance, which I've already listed, and you could have spared yourself the trouble.
ojosilva 5y ago
I meant to write most i7 machines with a GPU where I trained my models. My post was about the lack of adequate SDKs for the NE on the M1. I don't know why the fuck you grabbed that tiny fraction and just ran off with it like I was writing an appleboy marketing manifesto on the M1 prowess.
- okamiueru 5y ago
  I mean... you are doing what I find more than a few always seem to do on threads discussing the M1. Which is to subtly suggest that it is a computational powerhouse, with vague and non-verifiable metrics (your post that I originally replied to is a good example). Agreeing to disagree should be possible, and the request you got for a follow up to give some more specific details was polite, and should not have been that hard to deal with. It was also genuinely interested in an answer, so I question the appropriateness of the langue your responded with. And, I might also remind you that as far as answering the question, it did not. If you haven't already, I'd suggest looking at https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html. And I mean that too in a polite way, as it is easy to get carried away and assume the worst in anonymous conversations with strangers. So, to summarize. Apple originally made highly misleading statements on the computational power of the M1, and since then, this misconception is repeated quite often. After a while, it gets annoying to see new posts on HN, week after week. Now, alluding that an M1 is 3x faster at training models than discrete GPUs can only be true if it is a decade old hardware. And as that stands, your original comment was asked to be clarified. After all, it's not unheard of for M1 benchmarks to disable the discrete GPU of the PC it is compared to, for "fairness". Limiting the training to a single CPU core for "even more fairness" would be par for the course. So, I did not suggest you were an "appleboy", as you put it. I asked what kind of hardware you actually experienced a 3x speedup on, as the i7 goes back to 2009, and "GPU", well, further back. In any case, and this might come as a surprise, feel free to not answer. But, then, I can only wish that you refrain from making the effort at a rude response.