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I don't think I've ever used more than a gigabyte of RAM programming. I could even do it on a Raspberry Pi. What exactly in your workflow uses 64GB of RAM?

gambiting 10y ago
C++ games programming. Build process uses several gigabytes, but running the game in debug configuration takes 50-55GB because we store every allocation at the moment. If I need to run my own servers or bake data I go over that easily.
- Artemis2 10y ago
  Makes sense. Thank you!
- eridius 10y ago
  When you say "store every allocation" do you mean you never release anything, or do you just mean you store info about every allocation? If it's the former, that sounds kind of crazy, is it common for game developers to do that? If it's the latter, you could always write it to disk (which is what malloc stack logging does).
  - gambiting 10y ago
    We had a random memory corruption problem recently, so we started storing every allocation without releasing, to verify periodically. We do free up old memory, but only every 10 million allocations or so. Maybe it's not super common for games programming, but it's definitely common to not use ref counted pointers or anything that could help you here.
deleted 10y ago
[deleted]
majewsky 10y ago
I remember upgrading my notebook from 1 to 2 GB of RAM (back in 2009) to speed up Git. It really benefits from additional filesystem cache.
x0x0 10y ago
16g ram: perhaps 13g available to the user. If you run chrome/spotify/slack/an editor you're often left with only 8g useable. ml work commonly uses data that is 8g+ -- and regularly 32g+ -- just for the data itself. Yes you can work on remote servers but it's convenient to be able to work and develop locally.
chewxy 10y ago
machine learning stuff - whilst training datasets are usually cloud-deployed, dev data alone can use up a lot of RAM. I've recently started dumping my matrices to disk for dev work now. Or turn off Chrome and Firefox which turns out to be the largest memory sucks in my ubuntu machine

gambiting 10y ago

C++ games programming. Build process uses several gigabytes, but running the game in debug configuration takes 50-55GB because we store every allocation at the moment. If I need to run my own servers or bake data I go over that easily.

Artemis2 10y ago
Makes sense. Thank you!
eridius 10y ago
When you say "store every allocation" do you mean you never release anything, or do you just mean you store info about every allocation? If it's the former, that sounds kind of crazy, is it common for game developers to do that? If it's the latter, you could always write it to disk (which is what malloc stack logging does).
- gambiting 10y ago
  We had a random memory corruption problem recently, so we started storing every allocation without releasing, to verify periodically. We do free up old memory, but only every 10 million allocations or so. Maybe it's not super common for games programming, but it's definitely common to not use ref counted pointers or anything that could help you here.

deleted 10y ago

[deleted]

majewsky 10y ago

I remember upgrading my notebook from 1 to 2 GB of RAM (back in 2009) to speed up Git. It really benefits from additional filesystem cache.

x0x0 10y ago

16g ram: perhaps 13g available to the user. If you run chrome/spotify/slack/an editor you're often left with only 8g useable. ml work commonly uses data that is 8g+ -- and regularly 32g+ -- just for the data itself. Yes you can work on remote servers but it's convenient to be able to work and develop locally.

chewxy 10y ago

machine learning stuff - whilst training datasets are usually cloud-deployed, dev data alone can use up a lot of RAM. I've recently started dumping my matrices to disk for dev work now. Or turn off Chrome and Firefox which turns out to be the largest memory sucks in my ubuntu machine