System Description
Resource Limits per User
Each user has 100GB of persistent file storage. The following table outlines the resource allocations of each server option.
Resource |
Description |
|---|---|
CPU 4CPU/16GB |
You have access to:
This option is for basic CPU needs. |
A100 GPU, 2CPU/8GB |
You have access to:
This option is for AI, data analytics, and HPC workloads. It is optimized for single-precision calculations. |
Actual CPU Core and Memory Limits
Because they can vary based on system demand, it is useful to know your actual CPU and memory limits. These actual limits are hard limits that you cannot exceed. If a process uses more than your actual memory limit, the process will be ended/canceled.
Use the following Python script to see your actual CPU core and memory limits:
import os
print(f"memory = {int(os.environ.get('MEM_LIMIT'))/(1024**3)}GB")
print(f"cores = {os.environ.get('CPU_LIMIT')}")
# The output will look like this:
# memory = XX.0GB
# cores = X.0
Notebook Duration Limits
Notebooks are temporary and intended to last a maximum of 24 hours. Notebooks older than 24 hours may be ended without warning.
Notebooks run live in a web browser, if you close your web browser or lose your internet connection for more than 1 hour, your notebook and running processes may end. It is expected that running processes will continue if your connection is interrupted for less than 1 hour.
User Directory
Files in your user directory are persistent.
ICRN does not backup data, you are responsible for backing up your files.
Image Options
Python
The Python image is a JupyterLab environment with Python and Conda installed. Python is a general-purpose programming language. Conda is an open source package management system.
PyTorch
The PyTorch image is a JupyterLab environment with PyTorch installed. The GPU resource is recommended for this image. NVIDIA provides a brief overview of GPU computing at the beginning of the Using GPUs with Python webinar hosted by NCSA. You can view past recordings of this webinar, and others, in the HPC Moodle Past NCSA Training Events Repository.
R
The R image is a JupyterLab environment with R Kernel installed. This can be used for R development in the Jupyter interface. R is a programming language and software environment for statistical computing and graphics.
RStudio
The RStudio image has R, RStudio, and jupyter-rsession-proxy installed. Take a look at the RStudio Get Started Guide if you are new to using RStudio.