update gcp wiki doc
Create an account at Google Cloud https://cloud.google.com/
-Here's a [quickstart quide](https://cloud.google.com/compute/docs/quickstart-linux) to getting a machine running.
+When you have signed in, go to the [Getting Started](https://console.cloud.google.com/getting-started) page. Set your country and agree to the Terms of Service, then press "Agree and Continue".
-The smallest vCPU instance on GCP is more than enough for the toy data set. That's g1-small (Shared-core machine type with 0.5 vCPU, 1.70 GB of memory, backed by a shared physical core). At training time CPU usage peaks at about 10% of the available compute on that instance type. For a bigger data set, choose a faster machine.
+You should land on the Console Home screen.
-In the `management options` section, paste the script from below. Keep an eye on the Elpis wiki for information about the latest version of Elpis.
+Make a new project using the CREATE PROJECT link. Later, you can create new projects from the "Select a Project" option in the blue top bar.
+
+On the New Project screen, add a Project Name and press "Create".
+
+When the project has been created, the console will show the project's Dashboard.
+
+To add a server to the project, open the left side Navigation Menu and select "Compute Engine". Then select "VM Instances". If this is the first time your Google account has used Cloud Platform you may be offered a free trial! If so, go through the process of signing up for it. Otherwise, you may need to add billing details to access VM instances (TODO add more info about that). You will need to enter credit card details during the free trial opt-in process, but you won't be billed unless you turn on Automatic Billing.
+
+
+Now that your account has free trial or billing set up, the VM instances page should show "Create" and "Import" buttons.
+
+Click "Create"
+
++ Name it
++ Select a Region and Zone
++ Choose a machine size. The size will determine how much it will cost to run. The smallest vCPU instance on GCP is more than enough for the toy data set. That's first series N1 with g1-small (shared-core machine type with 0.5 vCPU, 1.70 GB of memory, backed by a shared physical core). At training time CPU usage peaks at about 10% of the available compute on that instance type. For a bigger data set, or for faster training & transcription time, choose a faster machine.
+
++ You may need to change the size of the boot disk if you expect to train with a large dataset.
++ Select HTTP and HTTPS traffic in the Firewall options
++ Click the "Management, security, disks, networking, sole tenancy" link.
+
+Paste the following code into the "Startup Script" box
```
sudo apt update
@@ -17,6 +38,11 @@ sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubun
sudo apt update
sudo apt install ./containerd.io_1.2.2-3_amd64.deb
sudo apt install -y docker-ce
-sudo docker run -d --rm -p 80:5000/tcp coedl/elpis:interspeech-19
+sudo docker run -d --rm -p 80:5000/tcp coedl/elpis:stable
```
+
+Then press "Create"
+
+
+It will take approximately 15 minutes for the machine to start up and install all the software.
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