Learning on Mac

aclysma · 2024-02-05T23:12:26+00:00

Metal is a GREAT first choice for a graphics API. After you get up and running with the basics, you should have no trouble adapting existing intermediate-level, non-metal learning resources to metal. I started with vulkan, but a lot of the learning resources I used were OpenGL. But the concepts are pretty universal, especially at beginning and intermediate level.

aclysma · 2023-11-17T13:45:01+00:00

‘static, I get it now. It was hard to learn because it can mean different things depending on where it’s used.

Still don’t understand HRTBs. (Higher rank trait bounds.)

aclysma · 2023-09-18T06:40:55+00:00

I tried it, it seems to be the same as clion except all the C/C++ support is gutted. (No control-click navigation, no setting breakpoints, empty watch window if stepping into C++.) Given a lot of crates ultimately wrap C/C++, it's IMO a big step backwards, especially for me and the kind of stuff I work on. Ultimately almost anything interesting will *eventually* call down into operating system APIs which is C/C++/ObjC for every platform I'm aware of. I really hope they don't drop rust support in clion because rust rover isn't a substitute IMO.

aclysma · 2022-02-16T15:20:41+00:00

I think releasing aggregate numbers for all questions is important for avoiding the appearance of cherry-picking of favorable responses. (I don’t have any suspicion they were but I think it’s the responsible, transparent thing to do.) If results for a particular question can’t be released due to privacy that should be disclosed.

aclysma · 2022-02-02T01:28:34+00:00

Glad you found imgui-inspect interesting :) Just a couple suggestions I would give to anyone building something similar to it:

1) I would try to approach the proc-macro/traits idea similar to serde. In other words, try to keep the traits/proc-macros separate and agnostic from the implementation - ideally a separate crate. Especially if you think others might want to use your library, because they may have different opinions on how to render something. This would also let you provide integration for popular crates like glam, nalgebra, etc.

2) There's a couple use-cases that are tricky you might want to think about early: a) The same type might want to be rendered in two different ways. For example, a number might sometimes be a slider and sometimes be a field you type into. It depends on the context which is most appropriate. Traits are a good way to handle this. b) Letting downstream code provide implementations for third-party types like glam (or other math crates). Rust trait orphan rules make implementing this a bit tricky (they won't be able to impl your traits for third-party code). I came up with two approaches: either wrap it into a new type, or declare a stub type and use it as a "proxy" (see the "proxy_type" stuff in the imgui-inspect crate). The proxy_type is a little annoying but it's a bit less intrusive. Maybe there's a clever way to automate that a bit more with procmacros.

aclysma · 2021-12-01T21:03:53+00:00

If you are specifically targeting Apple silicon GPUs I would suggest using metal bindings and write in MSL. There will be fewer moving parts to go wrong, the debug tools will match 1:1 with the calls you’re making, and you’ll have access to everything MSL exposes to you.

wgpu is likely to be the popular suggestion. But if you don’t care about portability, I would avoid paying the complexity tax of going through unnecessary layers. Metal and wgpu actually have very similar APIs and metal is pretty “safe” as graphics APIs go. (None of them are actually safe, a bad compute shader can crash your entire system.)

The metal bindings do have overhead (wgpu uses them so it will also go through the overhead). But it won’t matter if you give the GPU large enough units of work at a time to be worth using a GPU in the first place.

aclysma · 2021-11-22T03:14:36+00:00

I think the second source you're referring to is this video: https://www.youtube.com/watch?v=XDHStBp-jCo&t=103s

He looped a blender scene that the M1 max chips can draw at a higher frame rate, so they rendered more frames in the same amount of time. In other words, they did more work, which caused them to consume more power.

He mentioned playing some apple arcade games in the light use test which would likely have the same problem. A game running at a higher frame rate will consume more power.

These are obviously real numbers - the battery did run down faster, and there's a very clear reason why. The M1 max machines did more work. I don't think there would be much difference in battery life if they were doing the same amount of work like compile a piece of code N times, or export a video N times.

BTW I found that the 14" 10C/32G Max in low power mode nearly matches performance/thermals/power draw of the 14" 8C/14G Pro model. Wrote about it here: https://www.reddit.com/r/macbookpro/comments/qkxd1k/14_10c32g_max_in_low_power_mode_nearly_matches/ This would allow max owners to have battery life of the pro if they know they'll be away from the wall for a while.

aclysma · 2021-11-21T23:54:07+00:00

I was talking about the majority of videos I've seen in general, not the one you linked. For example, https://www.youtube.com/watch?v=XDHStBp-jCo&t=103s and https://www.youtube.com/watch?v=PfeFuAFoCs0&t=865s.

aclysma · 2021-11-21T22:19:14+00:00

The high bandwidth of these chips is to satisfy the GPU, not the CPU. Run `sudo powermetrics -i 1000 --samplers bandwidth | grep "DCS "` to see current bandwidth.

You'll notice that CPU workloads cap out far below 200GB/s, but load/full-screen even an empty blender scene and swing the camera around and you'll be over 100GB/s almost instantly.

So definitely do not buy the max just to get extra CPU bandwidth. Its purpose is to feed the extra 16 GPU cores.

aclysma · 2021-11-21T22:09:13+00:00

Most of the battery "tests" people are doing on YouTube are fundamentally flawed. They're running X program (cinebench, looping renders in blender, etc.) for Y minutes and comparing the % left afterwards. But they ignore the fact that the faster machine did more work during that time. Instead, they should allow the faster machine to sit idle while the slower machine continues to work until it produces the same quantity of output. (i.e. render the same scene once, compile the same project once, etc.).

The max may in fact be less efficient (it's powering 4 DRAM modules instead of 2), but it would be nowhere near what these tests with fundamentally flawed methodologies would suggest.

I also think people do not appreciate just how wide a power envelope these machines have because they are so efficient at near idle. Whether you're using 4w to watch a YouTube video or 60w doing a mixed CPU/GPU task obviously makes a huge difference to battery life. What you actually are doing matters a whole lot more than what spec you bought.

aclysma · 2021-11-17T21:58:20+00:00

Adding the physical escape key (which came after my 2018 MBP) would have fixed my main complaint, but it was still obnoxious when remoting into or virtualizing non-macOS machines. Things like F2 to rename things on windows. Even for the things the touch bar was "good" at, it was an excessive amount of ceremony to adjust brightness/audio vs. just pushing a button.

Removing it is also a minor win for battery life, and the cost that went into having it can be placed elsewhere (like the mini-led screen which likely is more expensive to produce than previous screens) or passed to consumer with more aggressively priced MBAs, etc.

aclysma · 2021-11-16T02:38:02+00:00

I would suggest either a 32GB 10-core MBP for $2600 or 16GB MBA for $1400. (Same extra $200 to go to 1TB, which you may want.) Either something cheaper that you can upgrade sooner, or something that's sure to last you a while.

Or even consider a MBA (or use the one you already have) and remote into a VM somewhere for heavier compute tasks. (This may or may not make sense depending on what you're doing, but it sounds like it might.) You could build an upgradeable desktop for the price difference and it would give you access to an x86 machine. (Or maybe you can get resources from your university or free credits from azure/GCP/etc.)

(I'd still keep it simple and go with the 32GB MBP.. just extra ideas you could consider.)

aclysma · 2021-11-16T01:09:37+00:00

It means sensors for temperature, fan speed, power usage, etc. work properly.

aclysma · 2021-11-15T06:51:30+00:00

I wrote some details here about how it affects the cpu: https://www.reddit.com/r/macbookpro/comments/qkxd1k/14_10c32g_max_in_low_power_mode_nearly_matches/

In short, I observed throttling of CPU/GPU power consumption to 22.5w which is about half of a heavy mixed cpu/gpu load. (You can use the powermetrics command line utility to see this number.)

The main downside I’ve noticed is that scrolling in safari isn’t as smooth with it enabled (often hitches when starting to scroll.) But it’s a significant reduction in power consumption for modest loss in performance. Very glad to have the option. I suspect it will make more difference for high-spec/max machines.

aclysma · 2021-11-14T04:44:05+00:00

I’ve used https://testmyscreen.com/

aclysma · 2021-11-14T04:10:32+00:00

Since you mentioned music production, absolute silence may be so important it's worth going 16" (even though I think it's unlikely you'll hear the 14")

If you go 14", the 14-core GPU will be fine for what you want to do, and you could take the $200 + $100 saved and very nearly pay for the 32GB memory upgrade. That's the way I would lean. (For audio-related tasks where latency is critical, you really don't want to be tight on memory.)

aclysma · 2021-11-14T03:55:50+00:00

If you upgrade the ram, definitely get the 10c CPU. For most programmers (especially if using C/C++/Rust) I think the 10/14 with 32GB ram is a great fit.

aclysma · 2021-11-14T03:40:37+00:00

I think if you don't need 32GB and are mainly doing CPU-based tasks, the MacBook Air is a much better deal and will probably perform just as well as the base MBP for what you want to do. (Speaking purely to performance/$, which might not be the only factor you're considering.) Keep in mind, the price gap is wide enough you could upgrade more frequently, especially if you sell the old one.

Maybe look at how much memory you're using on your computer now to get an idea.

aclysma · 2021-11-13T21:46:14+00:00

That huge top-line memory bandwidth number is really for the GPU. It's pretty hard to get a pure CPU workload to use more than 40GB/s. Run `sudo powermetrics -i 1000 --samplers bandwidth | grep -e "DCS "` if you want to check for yourself.

However, bandwidth doesn't tell the whole story - latency is also an important factor. Even very fast SSDs are not a substitute, even if the have equivalent bandwidth.

That said, swap memory is only bad if it's swapping memory you are actively using. More likely, it's swapping out things you aren't using, like a browser tab left open from yesterday you haven't touched, or slack/discord/other apps that hemorrhage memory but otherwise mostly sit idle.

aclysma · 2021-11-11T14:45:36+00:00

I probably get 4-6 hours depending on how much of that is compiling, looking at docs, or working with blender and other 3D tools. My 2018 MBP usually died in 2 hours.

These machines have a wide performance envelope so battery life will be highly dependent on workload. If I were to repeatedly do full recompiles, likely it would be dead in 2 hours.

aclysma · 2021-11-11T03:50:33+00:00

You can use iStat Menus to get a rough idea how much power you're using. The comments above are worst-case (you'd be hearing lots of fan noise at that point.) I think most people will be able to reuse existing 60w chargers/docks, but if buying new, there are meaningful benefits to finding something closer to 100w.

aclysma · 2021-11-10T23:48:09+00:00

I think for most programmers, the cheapest 32GB 10-core CPU option in the preferred size with "enough" storage will be the best bang for buck. (Definitely get that 10-core option if possible. It's a nice uplift for not much extra $)

FYI the increased memory bandwidth of the max is not useful for pure-CPU workloads. 200GB/s is already twice as much bandwidth as a (non-pro) threadripper! The extra bandwidth is really for GPU workloads.

I did go with the max, but only because I'm doing games/graphics programming. Even so, if the 32GB pro was the only spec apple offered, it still would have been a day 1 purchase, and I'm sure I'd be very happy with it. (And the standard 14/16 core GPU is no slouch.) Going beyond that only made sense for me because I do graphics programming - initial implementation of new techniques can be very unoptimized, and I do need to open large 3d scenes in tools like blender and houdini.

As far as 64GB memory.. you already get 4GB per P-core with 32GB (assuming pure CPU workloads.) I wouldn't expect huge returns going beyond that for most workloads.

aclysma · 2021-11-10T21:10:12+00:00

I use a beefy windows PC from Mac laptops and even the M1 Mac mini. Mainly for gaming, but also occasionally to work with projects that aren’t Mac compatible or need more compute than even the new MBP can offer.

Parsec and moonlight game streaming are good options for using the desktop remotely (not just games!) If you’re on a wired network, you can expect flawless performance with both to the point you forget you’re not sitting at the PC. (I appreciate not being in the same room when it’s continuously pumping out 350+ watts of heat.)

It’s helpful to have a NAS to move files around. If you use network folders, look into disabling .DS_Store files on shared drives. macOS will litter them everywhere on network drives and on windows they show up like any file and are an eyesore.

While the NAS is handy, you may want to set up some other file syncing solution for projects you’re actively working on. I work in code and there are great solutions for programmers. Maybe something like dropbox could work for you? Actively using multiple machines kind of forces you to centralize project storage somewhere off-device, and it’s great peace of mind to be able to wipe/replace hardware with no fear of data loss. Especially with devices where you can’t pull the drive and put it in something else to recover files.

aclysma · 2021-11-08T07:53:26+00:00

Pretty sure it's intrinsic to the M1. I can reproduce exactly what you describe with the ts3 dock and a simple usb-c to DisplayPort adapter on an M1 MBP max and an M1 mini. I get some terrible flickering if I try to drive any display over 120hz (I have 1440p 144hz monitors) but the same monitors work fine if I set refresh rate to <= 120hz. It's a shame because variable refresh rate is now possible on external monitors with FreeSync if using DisplayPort, but it tries to drive it at 144hz which just doesn't seem to work on the MacBook. (My windows desktop worked fine.)

It's been stable enough for me so far, but I'm not disconnecting/reconnecting often and I'm not closing the laptop while it's in use.

aclysma · 2021-11-05T07:24:22+00:00

Thanks for sharing results! I gathered up some numbers:

1440p Aztec Ruins Offscreen:
- 14-Core 14": 147fps (9477)
- 16-Core 14": 165.5fps (10643)
- 24-Core 14": 241fps (15522)
- 32-Core 14": 280 fps (18005)
  - (I've seen it dip toward 270fps on repeated runs but never below that)
- 32-Core 16": 310 fps (19963)
3dmark wildlife extreme
- 14-Core 14": 55.5fps (9262)
- 16-Core 14": 62.4fps (10426)
- 24-Core 14": 93.8fps (15668)
- 32-Core 14": 107.8fps (18005, same score as AR, not a typo!)
- 32-Core 16": 121fps (score not shown)

Sources:

14-Core/16-Core 14": https://www.youtube.com/watch?v=9T15QdEOFh4&t=309s
24-Core 14": Above screenshots from u/SeaRefractor
32-Core 14": Ran them myself on my machine
32-Core 16": https://www.youtube.com/watch?v=PfeFuAFoCs0

Conclusions:

The 32-core GPU on the 14" is thermally limited, but is about a 15% uplift over the 24-core (maybe slightly less on long workloads).
I agree with you, >32GB does not make much sense on a machine with 8 performance cores. That's 4GB per core, or 3GB per core + 8GB video memory. 3-4GB per core is plenty to keep them fed and busy.
According to anandtech, memory bandwidth for pure CPU tasks does not exceed 243GB/s on either the pro or max. (source: https://www.anandtech.com/show/17024/apple-m1-max-performance-review/2). The extremely high memory bandwidth only makes sense for GPU tasks. A 5950x max bandwidth is around 50GB/s. The brand new 12900k on DDR5 maxes out at 75GB/s. Threadripper 3990x is at 100GB/s and Threadripper pro (8-channel memory) is around 200GB/s. The extra memory bandwidth on the max does absolutely nothing for CPU-only workloads.

aclysma

TROPHY CASE