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From the notes: > CUDA 10.2 (Toolkit and NVIDIA driver) is the last release to support macOS for developing and running CUDA applications. Support for macOS will not be available starting with the next release of CUDA.
Earlier quoted context omitted.
Well, then you need to look a little bit longer around the market. At work we use Eurocom laptops with desktop-grade i7 and i9s rated at 90W of power - and we use them for conferences and trade shows to run our demonstrations, they do absolutely fine under full load. Sure they weigh about 5KG, but that's absolutely fine for the target use. I hope that answers the question of "why would you possibly want to do that".…
Those Eurocom laptops look neat, thanks for the tip. I'm just a bit surprised if they manage to squeeze out significantly better thermal performance than Dell does out of a similarly bulky laptop. Have you actually verified the core frequencies over time with a tool like CPU-z when running a workload that pegs all cores at 100%? The Precision model I have doesn't stutter or feel any slower under load. I've never mana…
As an example - the CPU in the Razer Blade is an i7-8565U, with base speed 1.8GHz, turbo speed 4.6GHz. Under maximum load I'll see it jump to 4.6GHz briefly, and then settle at 3.2GHz where it will remain indefinitely. Sure, the CPU has "throttled" down from its maximum turbo speed, but it's stable at 3.2GHz on default cooling. In comparison, I used to own an MSI GT63R with a quad core i7(2630QM if I remember correctly) and that CPU would "throttle" by regularly falling down to 400-600MHz(!!!) as a result of stretched thermals. It was not "stable" at neither its base nor turbo speeds. That behaviour still happens(in the mentioned Air, or an XPS 15 for instance) but there are definitely laptops which don't do that at all.
Why doesn't apple support NVIDIA though? Considering the whole ML and AI community use only NVIDIA GPUs, it sucks that we can't use apple laptops for the same.
I think for the larger models now it's more likely people are remotely logging into GPU clusters at this point. I don't think it will be that big of a change.
I'm optimistic about Nvidia eGPUs, but will be awhile to smooth out.
I'm using CUDA under Ubuntu, and have noticed that the CUDA library uninstalls itself every so often. Has anyone else experienced this?
First an optional prerequisite, for updated video drivers:
``` sudo apt-get install -y software-properties-common && sudo add-apt-repository -y ppa:graphics-drivers/ppa && sudo apt-get update && sudo apt-get install -y nvidia-driver-NNN ``` (Eg, nvidia-driver-435)
This is sometimes a required prerequisite, because these drivers have 32bit and 64bit binaries in them where the ones from nvidia's website or normal apt packages only have the 64bit drivers. (Eg, it's a requirement for Steam and many video games, which will suddenly stop working when CUDA is installed.)
Then there is CUDA itself:
``` sudo apt-get install -y gnupg2 curl ca-certificates && curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/ubu... | sudo apt-key add - && sudo echo "deb https://developer.download.nvidia.com/compute/machine-learni... /" > /etc/apt/sources.list.d/nvidia-ml.list && sudo apt-get update && sudo apt-get install -y nvidia-cuda-toolkit libcudnn7 libcudnn7-dev ``` (If also using cudnn.)
Also note: NVIDIA currently doesn't officially support Ubuntu 19, but their 18.04 repo works perfectly for 19. In the future you can always try grabbing from https://developer.download.nvidia.com/compute/cuda/repos/ubu... instead.
So what do people here use to learn/fool around with GPU-dependent ML stuff (non production use cases)? A non Mac laptop? Or do you do it all in the cloud? Using the cloud presumably gets expensive over time and I also would think that the overhead of dealing with a cloud setup and all the associated legwork to get started can be frustrating compared to working locally.
So what do people here use to learn/fool around with GPU-dependent ML stuff (non production use cases)? A non Mac laptop? Or do you do it all in the cloud? Using the cloud presumably gets expensive over time and I also would think that the overhead of dealing with a cloud setup and all the associated legwork to get started can be frustrating compared to working locally.
If you're doing anything process intensive, gpu or cpu, you'll want a desktop or cloud. Sure, some laptops are fast, but they head up, so there isn't much of a way around it.
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NVidia didn't want to pay for failing NVidia chips in MacBooks when they had problems with their manufacturing over half a decade ago and since then Apple tries everything to make NVidia's and its customers' life difficult.
Weren't these chips failing because of bad thermal design of the enclosure?
Earlier quoted context omitted.
Those Eurocom laptops look neat, thanks for the tip. I'm just a bit surprised if they manage to squeeze out significantly better thermal performance than Dell does out of a similarly bulky laptop. Have you actually verified the core frequencies over time with a tool like CPU-z when running a workload that pegs all cores at 100%? The Precision model I have doesn't stutter or feel any slower under load. I've never mana…
Right, let's clarify what I mean by "throttling". All intel CPUs have base and turbo speeds, and the turbo speeds usually only apply to a single core or to multiple while there is thermal headroom. By "throttling" I do mean the CPU falling below its base frequency to protect itself, I don't mean the turbo frequency falling down under load, that's normal and happens even on desktop CPUs with ample cooling. As an examp…
Intel will publish as you say a base speed of 1.8 GHz, then a single core Turbo speed of 4.6 GHz and also an all-core Turbo speed of 4.2 GHz (numbers made up, but something like this). If sufficient cooling is available, the CPU should be able to sustain the all-core Turbo number indefinitely. If it can't, I call that throttling. It can be mild (if you go from 4.2 to 3.2) or severe (if you go from 4.2 to 1.8). A colleague has the XPS 15 (well, the Precision equivalent) and he's never seen it drop below base clock, the problem with it is that base is something ridiculously low like 1.2 GHz. If a machine drops below base freq. due to thermal issues, it has been designed ver wrongly.
Our workstations with water cooling run at maximum all-core Turbo freq. for days on end. Those CPUs do exceed the specified TDP when doing so, which is fine as long as the cooler can easily dissipate that heat. And you can get water coolers that support 500W TDP, so no worries.
The only guarantee Intel makes is that the processor will stay within TDP when running at the base clock. What's happening when your laptop goes briefly to 4.2 GHz is that it exceeds both the Intel-stated TDP and the cooling system TDP. Then it throttles back to 3.2 GHz, which is a little below the cooling system TDP but above the processor TDP. In a laptop like the XPS 15, the cooling system TDP is only a little higher than Intel-stated TDP.
The momentary thermal headroom between what the CPU puts out at max Turbo and the cooling system TDP is provided by the heat capacity of the metal in the heatsink/heatpipe.
[1] https://clojurecl.uncomplicate.org/articles/getting_started....