Memory Bound Computations

We will start by cloning the MemoryBoundComputations repo, and follow the exercises/guidelines.txt.

You can also directly download a the slides or a snapshot of the repository .

Logging into remote machines

Two virtual machines with slightly more computing power than the notebooks are provided. They can be optionally used for some exercises.

An ssh key should be used to login into those machines. Paste the following code into a terminal:

(mkdir -p ~/.ssh && cd ~/.ssh && wget http://ipv4.in.waw.pl/~zbyszek/aspp/{config,known_hosts,id_rsa,id_rsa.pub} && chmod go= id_*)
ssh-add
  

After that, you should be able to log into aspp1 and aspp2 machines, using

ssh userX@aspp1

or

ssh userX@aspp2

User mapping:

  • laptop 1 → user0@aspp1
  • laptop 2 → user1@aspp1
  • laptop 3 → user2@aspp1
  • laptop 4 → user3@aspp1
  • laptop 5 → user4@aspp1
  • laptop 6 → user5@aspp1
  • laptop 7 → user6@aspp1
  • laptop 8 → user7@aspp1
  • laptop 9 → user8@aspp1
  • laptop 10 → user9@aspp1
  • laptop 11 → user0@aspp2
  • laptop 12 → user1@aspp2
  • laptop 13 → user2@aspp2
  • laptop 14 → user3@aspp2
  • laptop 15 → user4@aspp2
  • laptop 16 → user5@aspp2
  • laptop 17 → user6@aspp2
Using the jupyter notebook

Jupyter notebooks are already running on the server (verify with

systemctl --user status nbserver@*.service

).

Special care must be taken to connect using the right ports. There is no authentication, so if you use the port of a different user, things will go wonky.

If N is your user number, use

ssh -L127.0.0.1:8000:127.0.0.1:800N userN@aspp1

or

ssh -L127.0.0.1:8000:127.0.0.1:800N userN@aspp2

then open http://localhost:8000/ in the browser.


Contact: python-info@g-node.org