3 ms·

Pointless, just spin up a GPU instance in AWS. I use a MBP for ML but anything that needs GPU is better off running OFF my laptop.

by hkchad 7y ago

throwawaysea 7y ago
I’m not an expert on this topic so apologies if this is a basic question. Isn’t it annoying / time intensive / costly to rely solely on cloud GPUs when trying to learn or have hobby projects in ML? Is it really so practical that a local GPU has no value?
- mchen076 7y ago
  "Isn’t it annoying / time intensive / costly to rely solely on cloud GPUs when trying to learn or have hobby projects in ML?" No, it's all of those things when you use them professionally as well. There's a couple of things that people (usually business/operations people) overlook with respect to the cloud. Let's take a look: 1. The cost of compute clouds grows exponentially with every addition. Need an SSD? Extra money. Need an extra large HDD? Extra money. Need it on a secure private network? Extra money. You can very easily rack up the cost of a single local GPU system per-user per-year if you work on the cloud as a large organization. 2. Security: The cloud causes a lot of privacy issues and security issues. Are you a government agency with confidential information? Do you need to keep exact track of where it is at all times? The cloud will never let you do this. 3. Connectivity: I've yet to have any cloud provider provide uptime on the level that a local GPU box can provide. Our record cloud down-time was over a week. For these reasons, in larger organizations, cloud tends to get a lot of push back. Unfortunately, this is largely ignored by executives who have drank the cool-aid from Microsoft and think "cloud is the future"
cirgue 7y ago
This is fair if you're working in an environment where you can do that, but if you're designing stuff for anyone in a highly regulated industry, which is increasingly where ML is making the big bucks, doing mission-critical ML on someone else's servers is a no-no. There is still very much a need for beefy GPUs in laptops.
- Blackstone4 7y ago
  Maybe if a company is making big bucks off ML and were highly regulated, you would have thought they could setup a GPU/ML server....
  - deleted 7y ago
    [deleted]
  - cirgue 7y ago
    One would think, no? Those pesky lawyers, IT governance people, and institutional inertia have a habit of spoiling everyone's fun.

Pointless, just spin up a GPU instance in AWS. I use a MBP for ML but anything that needs GPU is better off running OFF my laptop.

by hkchad 7y ago

Pointless, just spin up a GPU instance in AWS. I use a MBP for ML but anything that needs GPU is better off running OFF my laptop.

throwawaysea 7y ago

I’m not an expert on this topic so apologies if this is a basic question. Isn’t it annoying / time intensive / costly to rely solely on cloud GPUs when trying to learn or have hobby projects in ML? Is it really so practical that a local GPU has no value?

mchen076 7y ago
"Isn’t it annoying / time intensive / costly to rely solely on cloud GPUs when trying to learn or have hobby projects in ML?" No, it's all of those things when you use them professionally as well. There's a couple of things that people (usually business/operations people) overlook with respect to the cloud. Let's take a look: 1. The cost of compute clouds grows exponentially with every addition. Need an SSD? Extra money. Need an extra large HDD? Extra money. Need it on a secure private network? Extra money. You can very easily rack up the cost of a single local GPU system per-user per-year if you work on the cloud as a large organization. 2. Security: The cloud causes a lot of privacy issues and security issues. Are you a government agency with confidential information? Do you need to keep exact track of where it is at all times? The cloud will never let you do this. 3. Connectivity: I've yet to have any cloud provider provide uptime on the level that a local GPU box can provide. Our record cloud down-time was over a week. For these reasons, in larger organizations, cloud tends to get a lot of push back. Unfortunately, this is largely ignored by executives who have drank the cool-aid from Microsoft and think "cloud is the future"

cirgue 7y ago

This is fair if you're working in an environment where you can do that, but if you're designing stuff for anyone in a highly regulated industry, which is increasingly where ML is making the big bucks, doing mission-critical ML on someone else's servers is a no-no. There is still very much a need for beefy GPUs in laptops.

Blackstone4 7y ago
Maybe if a company is making big bucks off ML and were highly regulated, you would have thought they could setup a GPU/ML server....
- deleted 7y ago
  [deleted]
- cirgue 7y ago
  One would think, no? Those pesky lawyers, IT governance people, and institutional inertia have a habit of spoiling everyone's fun.