Differences

This shows you the differences between two versions of the page.

--- en:hpc [2022/04/14 13:24] – grikiete
+++ en:hpc [2022/07/04 08:20] – [Paketinis užduočių vykdymas (SLURM)] grikiete
@@ Line 1: / Line 1: @@
 ====== Description of the Equipment ======
-A Distributed Computing Network (DCN) is a specially designed network of computers capable of running applications that can exchange data efficiently.
+A High Performance Computing (HPC) is a specially designed network of computers capable of running applications that can exchange data efficiently.
-VU MIF PST consists of a supercomputer from the clusters (the first number is the actual and available amount):
+VU MIF HPC consists of a supercomputer from the clusters (the first number is the actual and available amount):
 ^Title ^Nodes ^CPU ^GPU ^RAM        ^HDD    ^Network ^Notes|
@@ Line 13: / Line 13: @@
 The processor below = CPU = core - a single core of the processor (with all hyperthreads if they are turned on).
+====== Software ======
+In **main** and **gpu** partitions there are installed [[https://docs.qlustar.com/Qlustar/11.0/HPCstack/hpc-user-manual.html|Qlustar 11]] OS. It is based on Ubuntu 18.04 LTS. In **power** partition there is installed Ubuntu 18.04 LTS.
+You can check the list of OS package with the command ''dpkg -l'' (in login node **hpc** or in **power** nodes).
+With the command [[https://sylabs.io/guides/3.2/user-guide/index.html|singularity]] it is possible to make use of ready-made copies of container files in directories ''/apps/local/hpc'', ''/apps/local/nvidia'', ''/apps/local/intel'', ''/apps/local/lang'' or to download from singularity and docker online repositories. You can also create your own singularity containers using the MIF cloud service.
+You can prepare your container with singularity, for example:
+<code shell>
+$ singularity build --sandbox /tmp/python docker://python:3.8
+$ singularity exec -w /tmp/python pip install package
+$ singularity build python.sif /tmp/python
+$ rm -rf /tmp/python
+</code>
+Similarly, you can use R, Julia or other containers that do not require root privileges to install packages.
+If you want to add OS packages to the singularity container, you need root/superuser privileges. With fakeroot, we simulate them, and copy the required library ''libfakeroot-sysv.so'' into the container, for example:
+<code shell>
+$ singularity build --sandbox /tmp/python docker://ubuntu:18.04
+$ cp /libfakeroot-sysv.so /tmp/python/
+$ fakeroot -l /libfakeroot-sysv.so singularity exec -w /tmp/python apt-get update
+$ fakeroot -l /libfakeroot-sysv.so singularity exec -w /tmp/python apt-get install python3.8 ...
+$ fakeroot -l /libfakeroot-sysv.so singularity exec -w /tmp/python apt-get clean
+$ rm -rf /tmp/python/libfakeroot-sysv.so /tmp/python/var/lib/apt/lists (you can clean up more of what you don't need)
+$ singularity build python.sif /tmp/python
+$ rm -rf /tmp/python
+</code>
+There are ready-made scripts to run your **hadoop** tasks using the [[https://github.com/LLNL/magpie|Magpie]] set in the directory ''/apps/local/bigdata''.
+With [[https://hpc.mif.vu.lt/hub/|JupyterHub]] you can run calculations with the python command line in a web browser and use the [[https://jupyter.org|JupyterLab]] environment. If you install your own JupyterLab environment in your home directory, you need to install the additional ''batchspawner'' package - this will start your environment, for example:
+<code shell>
+$ python3.7 -m pip install --upgrade pip setuptools wheel
+$ python3.7 -m pip install --ignore-installed batchspawner jupyterlab
+</code>
+Alternatively, you can use a container that you made via JupyterHub. In that container, you need to install the ''batchswapner'' and ''jupyterlab'' packages, and to create a script ''~/.local/bin/batchspawner-singleuser'' with execution permissions (''chmod +x ~/.local/bin/batchspawner-singleuser'').
+<code shell>
+#!/bin/sh
+exec singularity exec --nv myjupyterlab.sif batchspawner-singleuser "$@"
+</code>
+====== Registration ======
+  * **For VU MIF network users** - HPC can be used without additional registration if the available resources are enough (monthly limit - **100 CPU-h and 6 GPU-h**). Once this limit has been reached, you can request more by filling in [[https://forms.office.com/Pages/ResponsePage.aspx?id=ghrFgo1UykO8-b9LfrHQEidLsh79nRJAvOP_wV9sgmdUM0ZMR1FINFg3TzVaNlhDSEhUN1A3QTlVUC4u|ITOAC service request form]].
+  * **For users of the VU computer network** - you must fill in the [[https://forms.office.com/Pages/ResponsePage.aspx?id=ghrFgo1UykO8-b9LfrHQEidLsh79nRJAvOP_wV9sgmdUM0ZMR1FINFg3TzVaNlhDSEhUN1A3QTlVUC4u|ITOAC service request form]] to get access to MIF HPC. After the confirmation of your request, you must create your account in [[https://hpc.mif.vu.lt|Waldur portal]]. More details read [[waldur|here]].
+  * **For other users (non-members of the VU community)** - you must fill in the [[https://forms.office.com/Pages/ResponsePage.aspx?id=ghrFgo1UykO8-b9LfrHQEidLsh79nRJAvOP_wV9sgmdUMDE1QUo3Slo3UVYwTjM4TDMyTEdZT0tSNi4u|ITOAC service request form]] to get access to MIF HPC. After the confirmation of your request, you must come to VU MIF Didlaukio str. 47, Room 302/304 to receive your login credentials. Please arranged the exact time by phone + 370 5219 5005. With these credentials you are able to create an account in [[https://hpc.mif.vu.lt|Waldur portal]]. More details read [[waldur|here]].
+====== Connection ======
+You need to use SSH applications (ssh, putty, winscp, mobaxterm) and Kerberos or SSH key authentication to connect to **HPC**.
+If **Kerberos** is used:
+  * Log in to the Linux environment in a VU MIF classroom or public terminal with your VU MIF username and password or login to **uosis.mif.vu.lt** with your VU MIF username and password using **ssh** or **putty**.
+  * Check if you have a valid Kerberos key (ticket) with the **klist** command. If the key is not available or has expired, the **kinit** command must be used.
+  * Connect to the **hpc** node with the command **ssh hpc** (password must not be required).
+If **SSH keys** are used (e.g. if you need to copy big files):
+  * If you don't have SSH keys, you can find instructions on how to create them in a Windows environment **[[duk:ssh_key|here]]**
+  *     Before you can use this method, you need to log in with Kerberos at least once. Then create a ''~/.ssh'' directory in the HPC file system and put your **ssh public key** (in OpenSSH format) into the ''~/.ssh/authorized_keys'' file.
+  *     Connect with **ssh**, **sftp**, **scp**, **putty**, **winscp** or any other **ssh** protocol supported software to **hpc.mif.vu.lt** with your **ssh private key**, specifying your VU MIF user name. It should not require a login password, but may require your ssh private key password.
+The **first time** you connect, you **will not** be able to run **SLURM jobs** for the first **5 minutes**. After that, SLURM account will be created.
+====== Lustre - Shared File System ======
+VU MIF HPC shared file system is available in the directory ''/scratch/lustre''.
+The system creates directory ''/scratch/lustre/home/username'' for each HPC user, where **username** is the HPC username.
+The files in this file system are equally accessible on all compute nodes and on the **hpc** node.
+Please use these directories only for their purpose and clean them up after calculations.
+====== HPC Partition ======
+^Partition ^Time limit ^RAM	   ^Notes|
+^main             ^7d            ^7000MB  ^CPU cluster|
+^gpu              ^48h           ^12000MB ^GPU cluster|
+^power            ^48h           ^2000MB  ^IBM Power9 cluster|
+The time limit for tasks is **2h** in all partitions if it has not been specified. The table shows the maximum time limit.
+The **RAM** column gives the amount of RAM allocated to each reserved **CPU** core.
+====== Batch Processing of Tasks (SLURM) ======
+To use computing resources of the HPC, you need to create task scenarios (sh or csh).
+Example:
+<code shell mpi-test-job.sh>
+#!/bin/bash
+#SBATCH -p main
+#SBATCH -n4
+module load openmpi
+mpicc -o mpi-test mpi-test.c
+mpirun mpi-test
+</code>
+Pateikus paraišką ITAPC ir gavus teigimą sprendimą, reikia susikurti naudotoją https://hpc.mif.vu.lt/. Sukurtas naudotojas bus įtrauktas į atitinkamą projektą, kuris turės tam tikrą kiekį resursų. Norint naudoti projekto resursus atliekant skaičiavimus reikia nurodyti savo alokacijos numerį. Žemiau pateiktas pavyzdys su nustatytu alokacijos parametru "alloc_xxxx_projektas" (taikomas ne VU MIF naudotojams, VU MIF naudotojai -- account parametro nurodyti neturi).
+<code shell mpi-test-job.sh>
+#!/bin/bash
+#SBATCH --account=alloc_xxxx_projektas
+#SBATCH -p main
+#SBATCH -n4
+#SBATCH --time=minutes
+module load openmpi
+mpicc -o mpi-test mpi-test.c
+mpirun mpi-test
+</code>
+Jame kaip specialūs komentarai yra nurodymai užduočių vykdytojui.
+ -p short - į kokią eilę siųsti (main, gpu, power).
+ -n4 - kiek procesorių rezervuoti (**PASTABA:** nustačius naudotinų branduolių skaičių x, tačiau realiai programiškai išnaudojant mažiau, apskaitoje vis tiek bus skaičiuojami visi x "užprašyti" branduoliai, todėl rekomenduojame apsiskaičiuoti iš anksto).
+Užduoties pradinis einamasis katalogas yra dabartinis katalogas (**pwd**) prisijungimo mazge iš kur paleidžiama užduotis, nebent parametru -D pakeistas į kitą. Pradiniam einamajam katalogui naudokite PST bendros failų sistemos katalogus **/scratch/lustre**, nes jis turi egzistuoti skaičiavimo mazge ir ten yra kuriamas užduoties išvesties failas **slurm-JOBID.out**, nebent nukreiptas kitur parametrais -o arba -i (jiems irgi patariama naudoti bendrą failų sistemą).
+Suformuotą scenarijų siunčiame su komanda sbatch
+''$ sbatch mpi-test-job''
+kuri gražina pateiktos užduoties numerį **JOBID**.
+Laukiančios arba vykdomos užduoties būseną galima sužinoti su komanda squeue
+''$ squeue -j JOBID''
+Su komanda scancel galima nutraukti užduoties vykdymą arba išimti ją iš eilės
+''$ scancel JOBID''
+Jeigu neatsimenate savo užduočių **JOBID**, tai galite pasižiūrėti su komanda **squeue**
+''$ squeue''
+Užbaigtų užduočių **squeue** jau neberodo.
+Jeigu nurodytas procesorių kiekis nėra pasiekiamas, tai jūsų užduotis yra įterpiama į eilę. Joje ji bus kol atsilaisvins pakankamas kiekis procesorių arba kol jūs ją pašalinsite su **scancel**.
+Vykdomos užduoties išvestis (**output**) yra įrašoma į failą **slurm-JOBID.out**. Jei nenurodyta kitaip, tai ir klaidų (error) išvestis yra įrašoma į tą patį failą. Failų vardus galima pakeisti su komandos **sbatch** parametrais -o (nurodyti išvesties failą) ir -e (nurodyti klaidų failą).
+Daugiau apie SLURM galimybes galite paskaityti [[https://slurm.schedmd.com/quickstart.html|Quick Start User Guide]].