Cluster: mudanças entre as edições
Linha 29: | Linha 29: | ||
<pre> | <pre> | ||
CPU: Ryzen (32 and 2*24 cores) | CPU: Ryzen (32 and 2*24 cores) + AMD 16 cores | ||
RAM: 64 GB each | RAM: 64 GB each | ||
GPU: | GPU: hree nodes with NVIDIA CUDA | ||
Storage: storage Dell 12TB | Storage: storage Dell 12TB | ||
Conection inter-nodes: Gigabit | Conection inter-nodes: Gigabit |
Edição das 09h19min de 25 de janeiro de 2024
Clusters Ada and Lovelace - Instituto de Física UFRGS
The clusters are located at Instituto de Física da UFRGS, in Porto Alegre.
Infraestruture
Management Software
Slurm Workload Manager(https://slurm.schedmd.com/) Number of jobs per user controlled on demand. Number of users on 1/24/2023: 150
Hardware in ada nodes
CPU: 16 nodes x86_64 RAM: varies between 8 GB - 16 GB GPU: 3 nodes with NVIDIA CUDA Storage: storage Asustor 12TB Inter-node connection: Gigabit
Hardware in lovelace nodes
CPU: Ryzen (32 and 2*24 cores) + AMD 16 cores RAM: 64 GB each GPU: hree nodes with NVIDIA CUDA Storage: storage Dell 12TB Conection inter-nodes: Gigabit
Installed Software
OS: Debian 8 (in cluster ada) OS: Debian 12 (in cluster lovelace) Basic packages installed: gcc gfortran python: torch, numba julia conda compucel3d espresso gromacs lammps mesa openmpi povray quantum-espresso vasp
How to use
Conect to cluster-slurm
The clusters are accessible through server cluster-slurm.if.ufrgs.br (ou ada.if.ufrgr.br). To access through a unix-like system use:
ssh <user>@lovelace.if.ufrgs.br
Under windows you may use winscp.
If you are not registered, ask for registration sending an email to fisica-ti@ufrgs.br
Using softwares in the cluster
To execute a software in a cluster job this program must:
1. Be already installed
OR
2. Be copied to the user home
Ex:
scp my_programm <user>@cluster-slurm.if.ufrgs.br:~/
If you are compiling your program in the cluster, one option is to user gcc
.
Ex:
scp -r source-code/ usuario@cluster-slurm.if.ufrgs.br:~/ ssh <user>@cluster-slurm.if.ufrgs.br:~/ cd source-code gcc main.c funcoes.c
This will generate file a.out
, which is the executable.
Being accessible by methods 1 or 2, the program can be executed in the cluster through one JOB.
OBS: If you execute your executable without submitting as JOB, it will be executed in the server, not in the nodes. This is not recommended since the server computational capabilities are limited and you will be slowing down the server for everyone else.
Criating and executing a Job
Slurm manages jobs and each job represents a program or task being executed.
To submit a new job, you must create a script file describing the requisites and characteristics of the Job.
A typical example of the content of a submission script is below
Ex: job.sh
#!/bin/bash #SBATCH -n 1 # Number of cpus to be allocated (Despite the # these SBATCH lines are compiled by the slurm manager!) #SBATCH -N 1 # Nummber of nodes to be allocated (You don't have to use all requisites, comment with ##) #SBATCH -t 0-00:05 # Limit execution time (D-HH:MM) #SBATCH -p long # Partition to be submitted #SBATCH --qos qos_long # QOS # Your program execution commands ./a.out
In option --qos, use the partition name with "qos_" prefix:
partition: short -> qos: qos_short -> limit 2 weeks
partition: long -> qos: qos_long -> limit de 3 month
If you run on GPU, specify the "generic resource" gpu in cluster ada:
#!/bin/bash #SBATCH -n 1 #SBATCH -N 1 #SBATCH -t 0-00:05 #SBATCH -p long #SBATCH --qos qos_long # QOS #SBATCH --gres=gpu:1 # Comandos de execução do seu programa: ./a.out
To ask for a specific gpu:
#SBATCH --constraint="gtx970"
To submit the job, execute:
sbatch job.sh
Usefull commands
- To list jobs:
squeue
- To list all jobs running in the cluster now:
sudo squeue
- To delete a running job:
scancel [job_id]
- To list available partitions:
sinfo
- To list gpu's in the nodes:
sinfo -o "%N %f"
- To list characteristic of all nodes:
sinfo -Nel