- Using CUDA makes sense for massively parallelizable code, like matrix multiplication.
- But copying data from host memory (RAM) to GPU is slow.
- MATLAB has many CUDA aware functions. For testin, you can use MATLAB on sunna (node 01 - 08 only, please).
- Generating random numbers and copying it back to host RAM was seen to be about 3 times faster while using CUDA.
- But "raw" CUDA C/C++ needs a lot of boilerplate code to be written. Hecke tells me that this is changing/has changed a lot in newer versions of CUDA.
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Section "ServerLayout" | |
Identifier "Layout0" | |
Screen "left" 0 0 | |
Screen "center" RightOf "left" | |
Screen "right" RightOf "center" | |
InputDevice "Keyboard0" "CoreKeyboard" | |
InputDevice "Mouse0" "CorePointer" | |
Option "Xinerama" "true" | |
EndSection |
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sudo: false # ensures the new container based infrastructure is used. | |
language: python | |
cache: | |
directories: | |
- $HOME/.cache/pip | |
python: | |
- '2.7' | |
- '3.4' | |
addons: |
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#!/bin/sh | |
# squid server IP | |
SQUID_SERVER="192.168.1.5" | |
# Interface connected to Internet | |
INTERNET="enp3s1" | |
# Interface connected to LAN | |
LAN_IN="enp1s0" | |
# Squid port | |
SQUID_PORT="3128" | |
# DO NOT MODIFY BELOW |
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""" | |
Automatically setup external monitors at MOIA so that it's to the right of the | |
internal screen | |
Prerequisite: [displayplacer](https://github.com/jakehilborn/displayplacer) | |
```bash | |
brew tap jakehilborn/jakehilborn && brew install displayplacer | |
``` |