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Apple M1 Max Geekbench Score

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Re: Apple M1 Max Geekbench Score

#431

Post by smoldesu »

PragmaticPulp wrote: post #390
VortexDream wrote: post #325

Earlier quoted context omitted.

The fact that this beats AMDs top laptop CPU is actually a huge deal. And that's before considering battery life and thermals. I'll never buy an Apple computer, but I can't help but be impressed with what they've achieved here.

Don't get me wrong: It's impressive and I have huge respect for it. I also bought one. However, it would be surprising if Apple's new 5nm chip didn't beat AMD's older 7nm chip at this point. Apple specifically bought out all of TSMC's 5nm capacity for themselves while AMD was stuck on 7nm (for now). It will be interesting to see how AMD's new 6000 series mobile chips perform. According to rumors they might be launche…

This definitely is a factor. Another thing that people frequently overlook is how competitive Zen 2 is with M1: the 4800u stands toe-to-toe with the M1 in a lot of benchmarks, and consistently beats it in multicore performance.

Make no mistake, the M1 is a truly solid processor. It has seriously stiff competition though, and I get the feeling x86 won't be dead for another half decade or so. By then, Apple will be competing with RISC-V desktop processors with 10x the performance-per-watt, and once again they'll inevitably shift their success metrics to some other arbitrary number ("The 2031 Macbook Pro Max XS has the highest dollars-per-keycap ratio out of any of the competing Windows machines we could find!")

Re: Apple M1 Max Geekbench Score

#432

Post by munro »

bredren wrote: post #375
58028641 wrote: post #366

Earlier quoted context omitted.

OpenCL and OpenGL have been deprecated in favor of Metal. Geekbench also has a Metal compute benchmark.

Is there a metal benchmark? This is the score I’ve been most interested in.

Nay, there isn't one for the new M1 Max, but FWIW it's pretty comparable, but OpenCL is a bit faster than Metal.

* MacBook Pro (16-inch Late 2019) - Metal https://browser.geekbench.com/v5/compute/3139776 [31,937 metal score]

* MacBook Pro (16-inch Late 2019) - OpenCL https://browser.geekbench.com/v5/compute/3139756 [33,280 OpenCL score]

Re: Apple M1 Max Geekbench Score

#433

Post by derefr »

jjcon wrote: post #418
derefr wrote: post #410

Earlier quoted context omitted.

> an nvidia gpu will still run circles arounnd this thing Not for loading up models larger than 32GB it wouldn't. (They exist! That's what the "full-detail model of the starship Enterprise" thing in the keynote was about.) Remember that on any computer without unified memory, you can only load a scene the size of the GPU's VRAM. No matter how much main memory you have to swap against, no matter how many GPUs you thro…

Memory != Speed You could throw a TB of memory in something and it won't get any faster or be of any use for 99.99% of use cases. Large ML architectures don't need more memory, they need distributed processing. Ignoring memory requirements, GPT-3 would take hundreds of years to train on a single high end GPU (on say a desktop 3090 which is >10x faster than m1) which is why they aren't trained that way (and why NVidia…

I don't disagree that there are many use cases for which more memory has diminishing returns. But I would disagree that those encompass 99.99% of use cases. Not all problems are embarrassingly-parallel. In fact, most problems aren't embarrassingly parallel.

It's just that we mostly use GPUs for embarrassingly-parallel problems, because that's mostly what they're good at, and humans aren't clever enough by half to come up with every possible way to map MIMD problems (e.g. graph search) into their SIMD equivalents (e.g. matrix multiplication, ala PageRank's eigenvector calculation.)

The M1 Max isn't the absolute best GPU for doing the things GPUs already do well. But its GPU is a much better "connection machine" than e.g. the Xeon Phi ever was. It's a (weak) TPU in a laptop. (And likely the Mac Pro variant will be a true TPU.)

Having a cheap, fast-ish GPU with that much memory, opens up use-cases for which current GPUs aren't suited. In those use-cases, this chip will "run circles around" current GPUs. (Mostly because current GPUs wouldn't be able to run those workloads at any speed.)

Just one fun example of a use-case that has been obvious for years, yet has been mostly moot until now: there are database engines that run on GPUs. For parallelizable table-scan queries, they're ~100x faster still than even memory databases like memSQL. But guess where all the data needs to be loaded into, for those GPU DB engines to do their work?

You'd never waste $150k on an A100 just to host an 80GB database. For that price, you could rent 100 regular servers and set them up as memSQL shards. But if you could get a GPU-parallel-scannable 64GB DB [without a memory-bandwidth bottleneck] for $4000? Now we're talking. For the cost of one A100, you get a cluster of ~37 64GB M1 Max MBPs — that's 2.3TB of addressable VRAM. That's enough to start doing real-time OLAP aggregations on some Big-Ish Data. (And that's with the ridiculous price overhead of paying for a whole laptop just to use its SoC. If integrators could buy these chips standalone, that'd probably knock the pricing down by another order of magnitude.)

Re: Apple M1 Max Geekbench Score

#434

Post by traceroute66 »

PragmaticPulp wrote: post #245
blakesterz wrote: post #100

I just can't figure out what I'm missing on the "M1 is so fast" side of things. For years I worked* on an Ubuntu desktop machine I built myself. Early this year I switched to a brand new M1 mini and this this is slower and less reliable than the thing I built myself that runs Ubuntu. My Ubuntu machine had a few little issues every no and then. My Mini has weird bugs all the time. e.g. Green Screen Crashes when I have…

> I just can't figure out what I'm missing on the "M1 is so fast" side of things. Two reasons: 1. M1 is a super fast laptop chip. It provides mid-range desktop performance in a laptop form factor with mostly fanless operation. No matter how you look at it, that's impressive. 2. Apple really dragged their feet on updating the old Intel Macs before the transition. People in the Mac world (excluding hackintosh) were stu…

> Apple really dragged their feet on updating the old Intel Macs before the transition

There was a Twitter post doing the rounds which I cannot locate now as my Twitter-search-foo is not strong enough. :-(

To summarise the gist of it: The post was made by someone on the product development team for the newly released MacBook Pro models, they referred to it as multiple years in the making.

So it may well be Apple were dragging their feet for good reason. They knew what was coming and did not want to invest further in Intel related R&D and did not want to end up with warehouses full of Intel-based devices and associated service parts.

Re: Apple M1 Max Geekbench Score

#435

Post by [deleted] »

jjcon wrote: post #418
derefr wrote: post #410

Earlier quoted context omitted.

> an nvidia gpu will still run circles arounnd this thing Not for loading up models larger than 32GB it wouldn't. (They exist! That's what the "full-detail model of the starship Enterprise" thing in the keynote was about.) Remember that on any computer without unified memory, you can only load a scene the size of the GPU's VRAM. No matter how much main memory you have to swap against, no matter how many GPUs you thro…

Memory != Speed You could throw a TB of memory in something and it won't get any faster or be of any use for 99.99% of use cases. Large ML architectures don't need more memory, they need distributed processing. Ignoring memory requirements, GPT-3 would take hundreds of years to train on a single high end GPU (on say a desktop 3090 which is >10x faster than m1) which is why they aren't trained that way (and why NVidia…

[deleted]

Re: Apple M1 Max Geekbench Score

#436

Post by alienalp »

blakesterz wrote: post #100

I just can't figure out what I'm missing on the "M1 is so fast" side of things. For years I worked* on an Ubuntu desktop machine I built myself. Early this year I switched to a brand new M1 mini and this this is slower and less reliable than the thing I built myself that runs Ubuntu. My Ubuntu machine had a few little issues every no and then. My Mini has weird bugs all the time. e.g. Green Screen Crashes when I have…

Actually there is nothing to figure out. If limitations of macos and arm cpu is not issue for you and you want a lightweight laptop then you buy a m1 macbook. m1 macbook air first Apple product i bought and i also had latest gen ryzen laptop at that time (which was superior to intel). Simply there is nothing to compare. It is not an alternative to m1 cpu. At least 5 years behind it. Actually it looks like it will never possible for that architecture to catch up with arm for low tdp siutations. If you ever used last gen windows laptop you will know there are always bugs. And installing ubuntu on a latest gen machine. LOL. That won't make you happy even if it is possible. I also had an issue with bluetooth mouse being laggy. It seems like patched now. Bugs were really an issue with m1 cpu but i assume there shouldn't be much issues now.

Re: Apple M1 Max Geekbench Score

#437

Post by m15i »

cschmid wrote: post #426
m15i wrote: post #346

Earlier quoted context omitted.

It’s all about the RAM. 64GB would allow input of larger image sizes and/or nets with more parameters. Right now, the consumer card with the most RAM is the rtx 3090 which is only 24GB, and in my opinion overpriced and inefficient in terms of wattage (~350W). Even the ~$6000 RTX A6000 cards are only 48GB.

I don't think replacing a workstation with a Macbook because of RAM makes too much sense: If running one minibatch of your model already takes up all the memory you have, where would the rest of your training data sit? In the M1, you don't have a separate main memory. Also, software support for accelerated training on Apple hardware is extremely limited: Out of the main frameworks, only tensorflow seems to target it,…

Good points. I look forward to some benchmarks. Just hoping for an alternative to Nvidia sooner than later. Dreaming apple will solve it and offer a 1.5 TB mac pro.

Re: Apple M1 Max Geekbench Score

#438

Post by flatiron »

mvanbaak wrote: post #372
throwaway894345 wrote: post #234

Earlier quoted context omitted.

That's Docker for Mac versus native Docker. Docker only runs on Linux, so Docker for Mac spins up a linux VM to run your containers. When you mount your Ruby or Python projects into your containers, Docker for Mac marshals tons of filesystem events over the host/guest boundary which absolutely devastates your CPU. Docker for Mac is really just bad for your use case. No idea what's going on with the thumb drive, bluet…

> Docker for Mac is really just bad for your use case. Nah, not just for mac, docker is really just bad. period ;P

Docker is certainly a hammer that makes a lot of problems look like nails. Maybe too frequently. But you can’t really debate that it’s a really powerful hammer.

Re: Apple M1 Max Geekbench Score

#439

Post by hraedon »

Thaxll wrote: post #147
windowsrookie wrote: post #129

Earlier quoted context omitted.

Comparing the M1 to a 1080ti is ridiculous. The 1080ti draws 250+ watts. The M1 draws 10w in the MacBook Air. In the current market you can buy a MacBook Air (an entire laptop computer) for less than buying just a midrange GPU.

Well Apple compared themself to a 3080m which is faster than a 1080ti.

Apple compared the M1 Max to a 3080m. 4x the GPU cores and up to 8x the memory makes a difference, and it wouldn't be at all surprising to see that their numbers are accurate.

Re: Apple M1 Max Geekbench Score

#440

Post by jaimex2 »

blakesterz wrote: post #100

I just can't figure out what I'm missing on the "M1 is so fast" side of things. For years I worked* on an Ubuntu desktop machine I built myself. Early this year I switched to a brand new M1 mini and this this is slower and less reliable than the thing I built myself that runs Ubuntu. My Ubuntu machine had a few little issues every no and then. My Mini has weird bugs all the time. e.g. Green Screen Crashes when I have…

You more or less described how Apple hype works.

The M1 is fast like a Ferrari, it's expensive and nice in the brochure but you can't take it many places in real life let alone use more than 20% of its potential.

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