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[AWS] -- second call -- updated documentation #14

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4 changes: 2 additions & 2 deletions docs/aws/connection.md
Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@ Once your account has been enabled, you can connect to the cluster using ssh. Co
To create a direct connection, use the command below (using your specific cluster name if it differs from workshop-cluster).

```bash
ssh -i sshkey.pem username@ec2-44-209-227-16.compute-1.amazonaws.com
ssh -i id_rsa username@ec2-52-5-167-162.compute-1.amazonaws.com
```
This will open a direct, non-graphical connection in the terminal. To exit the remote terminal session, use the standard Linux command “exit”.

Expand All @@ -17,7 +17,7 @@ Alternatively, you may want to save the configuration of this connection (and cr
```bash
Host aws-ulhpc-access
User username
Hostname ec2-44-209-227-16.compute-1.amazonaws.com
Hostname ec2-52-5-167-162.compute-1.amazonaws.com
IdentityFile ~/.ssh/id_rsa
IdentitiesOnly yes
```
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2 changes: 1 addition & 1 deletion docs/aws/overview.md
Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,7 @@ After initial project selection by a steering committee that includes representa

## System description and environment

The AWS Parallel Cluster based on the new Graviton3 (all instances and storage located in US-EAST-1) will provide cloud computing services to Uni.lu that will support the development, design, and testing of numerical codes, which traditionally demands a lot of compute power. This will give researchers an accessible, easy-to-use, end-to-end environment in which they can validate their simulation codes on ARM64 architectures, including servers, personal computers, and Internet of Things (IoT). The cluster will consist in two main partitions and jobs will be submitted using the [Slurm scheduler](https://slurm.schedmd.com/documentation.html) :
The AWS Parallel Cluster based on the new [HPC-based Graviton3 instances](https://aws.amazon.com/ec2/instance-types/hpc7g/) (all instances and storage located in US-EAST-1) will provide cloud computing services to Uni.lu that will support the development, design, and testing of numerical codes, which traditionally demands a lot of compute power. This will give researchers an accessible, easy-to-use, end-to-end environment in which they can validate their simulation codes on ARM64 architectures, including servers, personal computers, and Internet of Things (IoT). The cluster will consist in two main partitions and jobs will be submitted using the [Slurm scheduler](https://slurm.schedmd.com/documentation.html) :



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