Run relax at Google Cloud Computing

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Background

This follows the same idea as from Run relax at cloud.sagemath.com

Make a rapid deployment of relax on a google computer cluster, and calculate for 2 months with 8 CPU's, for free.

Pricing

For this example of Google Cloud Computing, we wan't to have access to as many computer cores as possible

At November 2015, google give free trial of 300$. https://cloud.google.com/free-trial/

Note, there are some limitations:

For this time, the most important limitation is 8 CPUs.

8 CPU's

For the price calculation of:

  • 1 server
  • using Free: Debian, CentOS, ...
  • with a regular VM Class
  • Instance type of (HIGH CPU) n1-highcpu-8 (vCPUs: 8, RAM: 7.20 GB)
  • 0 SSD
  • Datacenter location United States
  • Average days per month each server is running: 1 days, per month.

This 1 day price was of November 2015, $8.06. Constantly running is $171.70 per month.

This essentially gives you 2 months of free computation with 8 CPU's.

Start free trial

Please first see this video:

Go to: https://cloud.google.com/free-trial/ and click Start your free trial.

You need to sign up with a credit card. To prevent mis-abuse from robots and hackers.

Then go to: https://console.developers.google.com

  • You should already have a project called My First Project.
  • Create a new project in top right corner of the browser under the dropdown of My First Project.
  • Call the new project name relax, Project ID relax-1, App Engine location at us-central. NOTE: App engine HAS TO BE located in united states, if datalab should be enabled later.

Create a Virtual Machine instance

Links 

# List all compute instances in the project
gcloud compute instances list
gcloud compute zones list
gcloud compute machine-types list | grep us-central1-f

# Create instance
gcloud compute instances create relax --zone us-central1-f --machine-type n1-highcpu-8 --image ubuntu-14-04 --boot-disk-size 10GB 
gcloud compute instances list

Then you can SSH into the instance 

PROJ=relax-1
ZONE=us-central1-f
PRID=relax
GCC=gcc
gcloud compute --project $PROJ ssh --zone $ZONE $PRID

Access Virtual Machine instance

Install packages at server

For rapid deployment use this command. This will install current version of relax and trunk.

See the install script here 

wget http://svn.gna.org/viewcvs/*checkout*/relax/trunk/devel_scripts/deploy_google_computing_ubuntu.sh
source deploy_google_computing_ubuntu.sh

# Or in one go
URL=http://svn.gna.org/viewcvs/*checkout*/relax/trunk/devel_scripts/deploy_google_computing_ubuntu.sh
eval "$(curl "$URL")"

Check installation of relax 

mpirun --np 8 relax_trunk --multi='mpi4py'
relax_trunk --time -x

Transfer files back and forth to the server

See here

Install gcloud on your local computer

See https://cloud.google.com/sdk/

On your own computer 

cd $HOME/Downloads
curl https://sdk.cloud.google.com | bash
source $HOME/.bash_profile
gcloud init

This will start a browser to authenticate you. When it ask for a ID, just write "test" and say no to cloning.

Then go to:

It could look like this. Try this in your own terminal. This should make some SSH keys and bring you to the server 

gcloud compute --project "relax-1" ssh --zone "us-central1-f" "relax"

This should bring you to the google server. 

lscpu
cat $HOME/.ssh/authorized_keys 
exit

# At your own computer
ls -l $HOME/.ssh/google*
cat $HOME/.ssh/config
ssh-add -l
ssh-add $HOME/.ssh/google_compute_engine
ssh-add -l

Copy files

See: https://cloud.google.com/sdk/gcloud/reference/compute/copy-files

The ssh command was 

bash
PROJ=relax-1
ZONE=us-central1-f
PRID=relax
GCC=gcc
gcloud compute --project $PROJ ssh --zone $ZONE $PRID
exit

We make a test file on our local conouter and copy it 

touch test.txt
gcloud compute --project $PROJ copy-files test.txt $PRID:~ --zone $ZONE

# Try a directory
mkdir testdir
cp test.txt testdir
gcloud compute --project $PROJ copy-files testdir $PRID:~ --zone $ZONE

# Back again
cd testdir
gcloud compute --project $PROJ copy-files $PRID:~/testdir . --zone $ZONE

ssh-config with gcloud

See https://cloud.google.com/sdk/gcloud/reference/compute/config-ssh

gcloud compute config-ssh makes SSHing to virtual machine instances easier by adding an alias for each instance to the user SSH configuration (~/.ssh/config) file. 

gcloud compute --project $PROJ config-ssh
cat $HOME/.ssh/config

# ssh in
ssh $PRID.$ZONE.$PROJ
exit

# Use sed to change value of your local computes ssh config file
grep "$PRID.$ZONE.$PROJ" $HOME/.ssh/config
sed "s/$PRID.$ZONE.$PROJ/$GCC/g" $HOME/.ssh/config
sed -i.bak "s/$PRID.$ZONE.$PROJ/$GCC/g" $HOME/.ssh/config
ls -l $HOME/.ssh/config*
grep "$GCC" $HOME/.ssh/config
ssh $GCC
exit

Use scp and rsync when gcloud has been ssh-config configured

#First fast check
touch test2.txt
scp test2.txt  $GCC:
ssh $GCC
ls
exit

# Or use rsync
mkdir dirtest
rsync --progress -avzhe ssh ./dirtest $GCC:
ssh $GCC
ls
rmdir dirtest
exit

STOP the google instance after test to stop the billing of computation

See: https://cloud.google.com/compute/docs/instances/stopping-or-deleting-an-instance

By browser

Go to:

By terminal

# Get at list of projects
gcloud compute --project $PROJ instances list

# Start it, it takes 30 seconds.
gcloud compute --project $PROJ instances start --zone $ZONE $PRID
ssh $GCC
exit

# Stop it through terminal
gcloud compute --project $PROJ instances stop --zone $ZONE $PRID
# This should now not work
ssh $GCC

Upgrade account

To use 32 CPU's you need to upgrade your account

See

Deploy google datalab to your server

Read more here: http://techcrunch.com/2015/10/13/google-launches-cloud-datalab-an-interactive-tool-for-exploring-and-visualizing-data

Note: Cloud Datalab uses AppEngine and Managed VMs beta, which is available in the US region only.
You cannot change the location after the project has been created.
See Location at: https://appengine.google.com/

Start your server: 

gcloud compute --project $PROJ instances start --zone $ZONE $PRID
ssh $GCC

Cloud Datalab is deployed as an Google App Engine application module in a Google Developers Console project. Click here to → Enable the Google Compute Engine API.

Visit:

Do the following

  • Launch datalab
  • Sign in
  • Deploy to your project. This takes 10 min.

See also

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