Gila Documentation

docs/Documentation/Systems/Gila/filesystem.md

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+# Gila Filesystem Architecture Overview
+
+## Home Directories: /home
+
+`/home` directories are mounted as `/home/<username>`. To check your usage in your /home directory, visit the [Gila Filesystem Dashboard](https://influx.hpc.nrel.gov/d/ch4vndd/ceph-filesystem-quotas?folderUid=fexgrdi5pt91ca&orgId=1&from=now-1h&to=now&timezone=browser&tab=queries). You can also check your home directory usage and quota by running the following commands: 
+
+```
+# Check usage
+getfattr -n ceph.dir.rbytes <directory path>
+# Check quota
+getfattr -n ceph.quota.max_bytes <directory path>
+```
+
+If you need a quota increase in your home directory, please contact [[email protected]](mailto:[email protected]).
+
+## Project Storage: /projects
+
+Each active project is granted a subdirectory under `/projects/<projectname>`. There are currently no quotas on `/projects` directories. Please monitor your space usage at the [Gila Filesystem Dashboard](https://influx.hpc.nrel.gov/d/ch4vndd/ceph-filesystem-quotas?folderUid=fexgrdi5pt91ca&orgId=1&from=now-1h&to=now&timezone=browser&tab=queries). 
+
+Note that there is currently no `/projects/aurorahpc` directory. Data can be kept in your `/home` directory. 
+
+## Scratch Storage
+
+The scratch filesystem on Gila is a spinning disk Ceph filesystem, and is accessible from login and compute nodes. The default writable path for scratch use is `/scratch/<username>`. 
+
+!!! warning
+    Data in `/scratch` is subject to deletion after 28 days. It is recommended to store your important data, libraries, and programs in your project or home directory. 
+
+## Temporary space: $TMPDIR 
+
+When a job starts, the environment variable `$TMPDIR` is set to `/scratch/<username>/<jobid>` for the duration of the job. This is temporary space only, and should be purged when your job is complete. Please be sure to use this path instead of `/tmp` for your tempfiles.
+
+There is no expectation of data longevity in the temporary space, and data is purged once a job has completed. If desired data is stored here during the job, please be sure to copy it to a project or home directory as part of the job script before the job finishes.
+
+## Mass Storage System
+
+There is no Mass Storage System for deep archive storage from Gila.
+
+## Backups and Snapshots
+
+There are no backups or snapshots of data on Gila. Though the system is protected from hardware failure by multiple layers of redundancy, please keep regular backups of important data on Gila, and consider using a Version Control System (such as Git) for important code. 

docs/Documentation/Systems/Gila/index.md

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+
+# About Gila
+
+Gila is an OpenHPC-based cluster. Most [nodes](./running.md#gila-compute-nodes) run as virtual machines, with the exception of the Grace Hopper nodes, in a local virtual private cloud (OpenStack). Gila is allocated for NLR workloads. Check back regularly as the configuration and capabilities for Gila are augmented over time.
+
+
+## Gila Access and Allocations
+
+ **A specific allocation is not needed for NLR employee use of Gila.** All NLR employees with an HPC account automatically have access to Gila and can use the *aurorahpc* allocation to run jobs. If you do not have an HPC account already and would like to use Gila, please see the [User Accounts](https://www.nrel.gov/hpc/user-accounts) page to request an account. 
+
+The aurorahpc allocation does have limited resources allowed per job. These limits are dynamic, and can be found in the MOTD displayed when you log in to Gila. Please note that this allocation is a shared resource. If excessive usage reduces productivity for the broader user community, you may be contacted by HPC Operations staff. If you need to use more resources than allowed by the aurorahpc allocation, or work with external collaborators, you can request a specific allocation for your project. For more information on requesting an allocation, please see the [Resource Allocation Requests](https://www.nrel.gov/hpc/resource-allocation-requests) page. 
+
+#### For NLR Employees:
+To access Gila, log in to the NLR network and connect via ssh to:
+
+    gila.hpc.nrel.gov
+
+To use the Grace Hopper nodes, connect via ssh to:
+
+    gila-arm.hpc.nrel.gov
+
+#### For External Collaborators:
+There are no external-facing login nodes for Gila. There are two options to connect:
+
+1. Connect to the [SSH gateway host](https://www.nrel.gov/hpc/ssh-gateway-connection.html) and log in with your username, password, and OTP code. Once connected, ssh to the login nodes as above.
+1. Connect to the [HPC VPN](https://www.nrel.gov/hpc/vpn-connection.html) and ssh to the login nodes as above.
+
+## Get Help with Gila
+
+Please see the [Help and Support Page](../../help.md) for further information on how to seek assistance with Gila or your NLR HPC account. 
+
+## Building Code
+
+Do not build or run code on login nodes. Login nodes have limited CPU and memory available. Use a compute node or GPU node instead. Simply start an [interactive job](../../Slurm/interactive_jobs.md) on an appropriately provisioned node and partition for your work and do your builds there.
+

docs/Documentation/Systems/Gila/modules.md

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+# Modules on Gila
+
+On Gila, modules are deployed and organized slightly differently than on other NLR HPC systems. 
+While the basic concepts of using modules remain the same, there are important differences in how modules are structured, discovered, and loaded. These differences are intentional and designed to improve compatibility, reproducibility, and long-term maintainability. The upcoming sections of this document will walk through these differences step by step.
+
+The module system used on this cluster is [Lmod](../../Environment/lmod.md).
+
+When you log in to Gila, three modules are loaded automatically by default:
+
+1. `Core/25.05`
+2. `DefApps`
+3. `gcc/14.2.0`
+
+!!! note
+    The `DefApps` module is a convenience module that ensures both `Core` and `GCC` are loaded upon login or when you use `module restore`. It does not load additional software itself but guarantees that the essential environment is active.
+
+## x86 vs ARM 
+
+Gila has two separate module stacks, one for each hardware architecture. The appropriate stack is automatically loaded based on which login node you use.
+The two hardware stacks are almost identical in terms of available modules. However, some modules might be missing or have different versions depending on the architecture. For requests regarding module availability or version changes, please email [HPC-Help](mailto:[email protected]).
+
+To ensure proper module compatibility, connect to the login node corresponding to your target compute architecture:
+
+- **x86 architecture**: Use `gila.hpc.nrel.gov` 
+- **ARM architecture**: Use `gila-arm.hpc.nrel.gov` (Grace Hopper nodes)
+
+
+!!! warning
+    Do not submit jobs to Grace Hopper (ARM) compute nodes from the x86 login node, or vice versa.
+
+## Module Structure on Gila
+
+Modules on Gila are organized into two main categories: **Base Modules** and **Core Modules**. This structure is different from many traditional flat module trees and is designed to make software compatibility explicit and predictable.
+
+### Base Modules
+
+**Base modules** define the *software toolchain context* you are working in. Loading a base module changes which additional modules are visible and available.
+
+Base modules allow users to:
+
+* **Initiate a compiler toolchain**
+    * Loading a specific compiler (for example, `gcc` or `oneapi`) establishes a toolchain
+    * Once a compiler is loaded, only software built with and compatible with that compiler becomes visible when running `ml avail`
+    * This behavior applies to both **GCC** and **Intel oneAPI** toolchains
+
+* **Use Conda/Mamba environments**
+    * Loading `miniforge3` enables access to Conda and Mamba for managing user-level Python environments
+
+* **Access installed research applications**
+    * Loading the `application` module exposes centrally installed research applications
+
+* **Enable CUDA and GPU-enabled software**
+    * Loading the `cuda` module provides access to CUDA
+    * It also makes CUDA-enabled software visible in `module avail`, ensuring GPU-compatible applications are only shown when CUDA is loaded
+
+In short, **base modules control which families of software are visible** by establishing the appropriate environment and compatibility constraints.
+
+### Core Modules
+
+**Core modules** are independent of any specific compiler or toolchain.
+
+They:
+
+* Do **not** rely on a particular compiler
+* Contain essential utilities, libraries, and tools
+* Are intended to work with **any toolchain**
+
+Core modules are typically always available and can be safely loaded regardless of which compiler, CUDA version, or toolchain is active.
+
+This separation between Base and Core modules ensures:
+
+* Clear compiler compatibility
+* Reduced risk of mixing incompatible software
+* A cleaner and more predictable module environment
+
+## Module Commands: restore, avail, and spider
+
+### module restore
+
+The `module restore` command reloads the set of modules that were active at the start of your login session or at the last checkpoint. This is useful if you have unloaded or swapped modules and want to return to your original environment.
+
+Example:
+
+```bash
+module restore
+```
+
+This will restore the default modules that were loaded at login, such as `Core/25.05`, `DefApps`, and `gcc/14.2.0`.
+
+### module avail
+
+The `module avail` command lists all modules that are **currently visible** in your environment. This includes modules that are compatible with the loaded compiler, MPI, or CUDA base modules.
+
+Example:
+
+```bash
+module avail
+```
+
+You can also search for a specific software:
+
+```bash
+module avail python
+```
+
+### module spider
+
+The `module spider` command provides a **complete listing of all versions and configurations** of a software package, including those that are **not currently visible** with `module avail`. It also shows **which modules need to be loaded** to make a specific software configuration available.
+
+Example:
+
+```bash
+module spider python/3.10
+```
+
+This output will indicate any prerequisite modules you need to load before the software becomes available.
+
+!!! tip
+    Use `module avail` for quick checks and `module spider` when you need full details or to resolve dependencies for specific versions.
+
+## MPI-Enabled Software
+
+MPI-enabled software modules are identified by a `-mpi` suffix at the end of the module name.
+
+Similar to compiler modules, MPI-enabled software is **not visible by default**. These modules only appear after an MPI implementation is loaded. Supported MPI implementations include `openmpi`, `mpich`, and `intelmpi`.
+
+Loading an MPI implementation makes MPI-enabled software built with that specific MPI stack available when running `module avail`.
+
+This behavior ensures that only software built against the selected MPI implementation is exposed, helping users avoid mixing incompatible MPI libraries.
+
+### Example: Finding and Loading MPI-Enabled HDF5
+
+Use `module spider` to find all available variants of **HDF5**.
+
+```bash
+[USER@gila-login-1 ~]$ ml spider hdf5
+  hdf5:
+--------------------------------------------
+    Versions:
+      hdf5/1.14.5
+      hdf5/1.14.5-mpi 
+```
+
+Each version of **HDF5** requires dependency modules to be loaded before it becomes available. 
+Please refer to the [module spider section](modules.md#module-spider) for more details.
+
+To find the dependencies needed for `hdf5/1.14.5-mpi`:
+
+```bash
+[USER@gila-login-1 ~]$ ml spider hdf5/1.14.5-mpi
+
+  hdf5:
+--------------------------------------------
+    You will need to load all module(s) on one of the lines below before the 'hdf5/1.14.5-mpi' module is available to load.
+      gcc/14.2.0  openmpi/5.0.5
+      oneapi/2025.1.3  oneapi/mpi-2021.14.0
+      oneapi/2025.1.3  openmpi/5.0.5
+```
+
+Before loading the dependencies:
+
+```bash
+[USER@gila-login-1 ~]$ ml avail hdf5
+--------------- [ gcc/14.2.0 ] -------------
+  hdf5/1.14.5
+```
+
+This version of **HDF5** is not MPI-enabled. 
+
+After loading the dependencies, both versions are now visible: 
+
+```bash
+[USER@gila-login-1 ~]$ ml gcc/14.2.0 openmpi/5.0.5
+[USER@gila-login-1 ~]$ ml avail hdf5
+--------------- [ gcc/14.2.0, openmpi/5.0.5 ] -------------
+  hdf5/1.14.5-mpi
+--------------- [ gcc/14.2.0 ] -------------
+  hdf5/1.14.5
+```
+
+
+!!! tip
+    To determine whether a software package is available on the cluster, use `module spider`. This command lists **all available versions and configurations** of a given software, including those that are not currently visible with `module avail`.
+
+    To find out which modules must be loaded in order to access a specific software configuration, run `module spider` using the **full module name**. This will show the required modules that need to be loaded to make that software available.
+
+
+## Containers
+
+Container tools such as **Apptainer** and **Podman** do not require module files on this cluster. They are available on the system **by default** and are already included in your `PATH`.
+
+This means you can use Apptainer and Podman at any time without loading a specific module, regardless of which compiler, MPI, or CUDA toolchain is currently active.
+
+
+## Building on Gila
+
+Building on Gila should be done on compute nodes and **NOT** login nodes. 
+Some important build tools are not available by default and require loading them from the module stack. 
+
+These build tools are: 
+
+- perl
+- autoconf
+- libtool
+- automake
+- m4
+
+Please see [here](./running.md#example-compiling-a-program-on-gila) for a full example of compiling a program on Gila. 
+
+
+## Frequently Asked Questions
+
+??? note "I can't find the module I need."
+    Please email [HPC-Help](mailto:[email protected]). The Apps team will get in touch with you to provide the module you need.
+
+??? note "I need to mix and match compilers and libraries/MPI. How can I do that?"
+    Modules on Gila do not support mixing and matching. For example, if `oneapi` is loaded, only software compiled with `oneapi` will appear. If you require a custom combination of software stacks, you are encouraged to use **Spack** to deploy your stack. Please contact [HPC-Help](mailto:[email protected]) to be matched with a Spack expert.
+
+??? note "Can I use Miniforge with other modules?"
+    While it is technically possible, Miniforge is intended to provide an isolated environment separate from external modules. Be careful with the order in which modules are loaded, as this can impact your `PATH` and `LD_LIBRARY_PATH`.
+
+??? note "What if I want a different CUDA version?"
+    Other CUDA versions are available under **Core** modules. If you need additional versions, please reach out to [HPC-Help](mailto:[email protected]). Note that CUDA modules under CORE do **not** automatically make CUDA-enabled software available; only CUDA modules under **Base** modules will load CUDA-enabled packages.