KO | EN

GitLite

Minimalist Open Source Repository Search Engine

gitlite — search

#dsh #ai-agents #dsh-plugin #codex #developer-tools #claude-code #windows #cli #desktop-app #typescript #rust #ai-agent

HPC4WC

★ 45 Open GitHub ↗

High Performance Computing for Weather and Climate

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# High-Performance Computing for Weather and Climate (HPC4WC)

[![License: GPLv3](https://img.shields.io/badge/License-GPLv3-blue?style=for-the-badge&labelColor=4c4c4c)](https://raw.githubusercontent.com/ofuhrer/HPC4WC/main/LICENSE)
[![Material checks](https://img.shields.io/github/actions/workflow/status/ofuhrer/HPC4WC/material.yml?branch=main&label=Tests&style=for-the-badge&labelColor=4c4c4c)](https://github.com/ofuhrer/HPC4WC/actions/workflows/material.yml)

High Performance Computing for Weather and Climate is a hands-on course on
performance-aware scientific programming. The material uses progressively more
complex versions of stencil computations to introduce hardware concepts,
parallel programming models, and performance-portable abstractions used in
weather and climate applications.

The course material is organized by day:

- [Day 1](day1): single-core performance, stencil programs, performance metrics,
  memory hierarchy, memory bandwidth, peak floating-point performance,
  arithmetic intensity, roofline model, array storage in memory, and
  data-locality optimizations such as blocking, fusion, and inlining.
- [Day 2](day2): shared-memory parallelism with OpenMP, speedup, Amdahl's law,
  parallelization, synchronization, and variable scoping.
- [Day 3](day3): distributed-memory parallelism with MPI, message passing,
  point-to-point communication, deadlock, non-blocking communication,
  gather/scatter operations, domain decomposition, halo points, and halo updates.
- [Day 4](day4): GPU programming, hybrid node architecture, high-level GPU
  programming with CuPy, data management, synchronization, vectorization,
  platform-agnostic code, and lower-level GPU programming.
- [Day 5](day5): high-level programming models, domain-specific languages,
  GT4Py, performance portability, and abstractions for stencil computations.

## Setup

Follow the [getting started guide](setup/01-getting-started.md) to set up the
course environment.

## Running Checks

Some course exercises require specific HPC hardware, compilers, MPI, GPUs, or a
CSCS/Alps environment. The repository also contains lightweight checks that can
run locally and in GitHub Actions without those systems.

Run the material check for all course days with:

```bash
python tools/check_material.py
```

This validates notebooks and course files, checks Python and shell syntax,
compiles selected Fortran/C++ material when suitable compilers are available,
verifies local notebook image references, and runs small smoke tests for selected
scripts. The same check runs in GitHub Actions. It is intentionally lightweight;
full performance runs and GPU/cluster-specific exercises should still be
validated in the appropriate course environment.

## Pre-commit Checks

The repository provides conservative pre-commit checks for course preparation:

```bash
python -m pip install pre-commit
pre-commit install
```

The hooks block generated solution bundles from being committed, verify that
generated student material is current for days that use generated student
material, and check formatting for Python tooling in `tools/`. They
intentionally do not auto-format notebooks or Fortran course material.

HPC4WC

Explore Similar Repositories

Was this content helpful?

Recent Feedback

Download README