This project allows the user to easy install and start a HPC cluster on Amazon’s Elastic Compute Cloud (EC2).

• Amazon AWS account (https://console.aws.amazon.com/)
• Second user Amazon AWS with AmazonEC2FullAccess

Connect to Security Credentials Amazon console.

• Users -> Create New Users -> Enter User Name -> Create
• Users -> Select the user -> Attach Policy -> AmazonEC2FullAcces
• Users -> Select the user -> Security Credentials -> Create Access Key -> Download Credentials.csv

Connect to AWS Amazon console for N. Virginia.

Launch new t2.micro istance of Ubuntu machine.

• Instances -> Launch Instance -> Select Ubuntu Server -> Select t2.micro (Free tier eligible) -> Review and Launch -> Create new keypair ssh access (store it and don't lost) -> Launch

Connect to the remote machine (start on N.Virginia).

• Instances -> Select the created machine -> Edit the Name field, naming this machine "Controller"
• Right click on the machine and select connect, follow the suggested steps. ssh -i "test.pem" [email protected]

Copy the credentials.csv on the machine.

scp -i "test.pem" credentials.csv [email protected]: Add to credentials.csv

AWS Account ID,Access key ID,Secret access key ID,X,Y You can find ID in My Security Credentials->Account Identifiers

Downloads the script and the config file.

wget https://raw.githubusercontent.com/spagnuolocarmine/amazonhpc/master/hpc_starcluster_setup.sh

wget https://raw.githubusercontent.com/spagnuolocarmine/amazonhpc/master/config

Connect through SSH to the "Controller" machine and run the installation script.

source hpc_starcluster_setup.sh

startcluster start test

startcluster terminate test

In the config file change the variable CLUSTER_SIZE .

This script use the t2.micro instance of EC2 eligible for free. In the section Limits you can see the maximum number of instances that is possible to run (default is 20). Is possible to require the limit increase to the Amazon support. With basic account you can use the t2.micro instance, but if you are student you can ask for some credits to run other kind of instances.

• start: Start a new cluster
• stop: Stop a running EBS-backed cluster
• terminate: Terminate a running or stopped cluster
• restart, reboot: Restart an existing cluster
• listclusters, lc: List all active clusters
• sshmaster, sm: SSH to a cluster's master node (-u sgeadmin)
• sshnode, sn: SSH to a cluster node
• put: Copy files to a running cluster
• get: Copy one or more files from a running cluster to your local machine

StarCluster Ubuntu 12.04 AMI

Software Tools for Academics and Researchers (STAR)

Homepage: http://star.mit.edu/cluster

Documentation: http://star.mit.edu/cluster/docs/latest

Code: https://github.com/jtriley/StarCluster

Mailing list: [email protected]

This AMI Contains:

• NVIDIA Driver 313.26
• NVIDIA CUDA Toolkit 5.0, V0.2.1221
• PyCuda/PyOpenCL 2012.1
• MAGMA 1.3.0
• Open Grid Scheduler (OGS - formerly SGE) queuing system
• Condor workload management system
• OpenMPI compiled with Open Grid Scheduler support
• OpenBLAS - Highly optimized Basic Linear Algebra Routines
• NumPy/SciPy linked against OpenBLAS
• Julia linked against OpenBLAS
• IPython 0.13 with parallel support
• and more! (use 'dpkg -l' to show all installed packages)

Open Grid Scheduler/Condor cheat sheet:

• qstat/condor_q - show status of batch jobs
• qhost/condor_status- show status of hosts, queues, and jobs
• qsub/condor_submit - submit batch jobs (e.g. qsub -cwd ./job.sh)
• qdel/condor_rm - delete batch jobs (e.g. qdel 7)
• qconf - configure Open Grid Scheduler system

1. Connect to the master of the HPC cluster from Controller machine.

starcluster sshmaster -u sgeadmin test

2. Create the file test.c

#include <mpi.h>
   #include <stdio.h>
   int main(int argc, char** argv) {
   // Initialize the MPI environment
        MPI_Init(NULL, NULL);
        // Get the number of processes
        int world_size;
        MPI_Comm_size(MPI_COMM_WORLD, &world_size);
        // Get the rank of the process
        int world_rank;
        MPI_Comm_rank(MPI_COMM_WORLD, &world_rank);
        // Get the name of the processor
        char processor_name[MPI_MAX_PROCESSOR_NAME];
        int name_len;
        MPI_Get_processor_name(processor_name, &name_len);
        // Print off a hello world message
        printf("Hello world from processor %s, rank %d"
               " out of %d processors\n",
               processor_name, world_rank, world_size);
        // Finalize the MPI environment.
        MPI_Finalize();
    }

3. Compile the file test.c in test.out

mpicc test.c -o test.out

4. Copy on all nodes the file, your node are named from 000 to N, (e.g. 001, 002...) see the file /etc/hosts

scp test.out nodeX:

5. Run the example

root@master:~# mpirun -np 10 -host node001,node002 a.out 
 Hello world from processor node001, rank 8 out of 10 processors
 Hello world from processor node001, rank 0 out of 10 processors
 Hello world from processor node002, rank 5 out of 10 processors
 Hello world from processor node001, rank 4 out of 10 processors
 Hello world from processor node002, rank 7 out of 10 processors
 Hello world from processor node001, rank 6 out of 10 processors
 Hello world from processor node002, rank 3 out of 10 processors
 Hello world from processor node001, rank 2 out of 10 processors
 Hello world from processor node002, rank 9 out of 10 processors
 Hello world from processor node002, rank 1 out of 10 processors```