2.5 Interactive Computing
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SDSC Summer Institute 2023
Session 2.5 Interactive Computing
Date: Monday, August 7, 2023
Content:
- Summary
- Reading and Presentations:
- Task 1: Clone the repo
- Task 2: Hands-on: Interactive Computing on CPU Node
- Task 3: Hands-on: Interactive Computing on GPU Node
- Task 4: Hands-on: Run GnuPlot on CPU
- Task 5: Examine NetCDF data on CPU
Summary: Interactive computing refers to working with software that accepts input from the user as it runs. This applies not only to business and office applications, such as word processing and spreadsheet software, but HPC use cases involving code development, real-time data exploration and advanced visualizations run across one or more compute nodes. Interactive computing is often used when applications require large memory, have large data sets that are not that practical to download to local devices, need access to higher core counts or rely on software that is difficult to install. User inputs are entered via a command line interface (CLI) or application GUI (e.g., Jupyter Notebooks, Matlab, RStudio). Actions are initiated on remote compute nodes as a result of user inputs. This session will introduce participants to advanced CI concepts and what’s going on "under the hood" when they are using interactive tools. Topics covered will include mechanisms for accessing interactive resources; commonalities and differences between batch and interactive computing; understanding the differences between web-based services and X11/GUI applications; monitoring jobs running on interactive nodes; overview of Open OnDemand portals.
Presented by: Mary Thomas (mpthomas @ucsd.edu)
Reading and Presentations:
- Lecture material:
- Presentation Slides: will be made available closer to the session
- Source Code/Examples: N/A
- SDSC HPC Training Examples Repo @ https://github.com/sdsc-hpc-training-org/hpctr-examples.git
- Expanse 101 tutorial: https://hpc-training.sdsc.edu/expanse-101/
TASK 1: Clone the repo
- Clone the SDSC HPC Training Examples Repo @ https://github.com/sdsc-hpc-training-org/hpctr-examples.git
TASK 2: Hands-on: Interactive Computing on CPU Node
Use the srun command to get an interactive CPU node:
[mthomas@login02 calc-prime]$ srun --partition=compute --pty --account=use300 --nodes=1 --ntasks-per-node=128 --mem=8G -t 00:30:00 --wait=0 --export=ALL /bin/bash
srun: job 24459379 queued and waiting for resources
srun: job 24459379 has been allocated resources
[mthomas@exp-6-16 calc-prime]$
- Set up the module ENV:
module purge
module load slurm
module load cpu
module load gcc/10.2.0
module load openmpi/4.1.1
- list the modules
[mthomas@exp-6-16 calc-prime]$ module list
Currently Loaded Modules:
1) slurm/expanse/21.08.8 3) gcc/10.2.0/npcyll4 5) openmpi/4.1.1/ygduf2r
2) cpu/0.17.3b (c) 4) ucx/1.10.1/dnpjjuc
Where:
c: built natively for AMD Rome
Run calc-prime from the command line
mpirun -np 16 ./mpi_prime 500000
07 August 2023 01:36:28 AM
PRIME_MPI
n_hi= 262144
C/MPI version
An MPI example program to count the number of primes.
The number of processes is 16
N Pi Time
1 0 0.000817
2 1 0.000583
4 2 0.000004
8 4 0.000004
16 6 0.000004
32 11 0.000004
64 18 0.000004
128 31 0.000005
256 54 0.000008
512 97 0.000018
1024 172 0.000054
2048 309 0.000189
4096 564 0.000638
8192 1028 0.002281
16384 1900 0.008125
32768 3512 0.029826
65536 6542 0.111391
131072 12251 0.415458
262144 23000 1.543699
524288 43390 23.354061
PRIME_MPI - Master process:
Normal end of execution.
07 August 2023 01:44:11 AM
TASK 3: Hands-on: Interactive Computing on GPU Node
Use the srun command to get an interactive GPU node:
srun --partition=gpu-debug --pty --account=use300 --ntasks-per-node=10 --nodes=1 --mem=96G --gpus=1 -t 00:30:00 --wait=0 --export=ALL /bin/bash
- Check that you are on an NVIDIA GPU:
[mthomas@exp-7-59 mpi]$ nvidia-smi
Mon Aug 7 01:51:59 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 515.65.01 Driver Version: 515.65.01 CUDA Version: 11.7 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Tesla V100-SXM2... On | 00000000:18:00.0 Off | 0 |
| N/A 34C P0 41W / 300W | 0MiB / 32768MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
[mthomas@exp-7-59 mpi]$
- Set up the module ENV:
module purge
module load gpu/0.15.4
module load gcc/7.2.0
module load cuda/11.0.2
module load slurm
[mthomas@exp-7-59 hello-world]$ module list
Currently Loaded Modules:
1) gpu/0.15.4 (g) 2) gcc/7.2.0 3) cuda/11.0.2 4) slurm/expanse/21.08.8
Where:
g: built natively for Intel Skylake
- cd to cuda/hello-world directory
- compile hello-world
nvcc -o hello_world hello_world.cu
- Run the hello-world applciation
[mthomas@exp-7-59 hello-world]$ ./hello_world
Hello, SDSC HPC Training World!
[mthomas@exp-7-59 hello-world]$
- Try this for addition