Merge pull request #1 from FluidNumerics/emprism

Emprism

.github/workflows/main-docs.yml

@@ -0,0 +1,30 @@
+name: Publish documentation
+on:
+  push:
+    branches:
+      - main
+
+jobs:
+  build:
+    name: Deploy docs
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout main
+        uses: actions/checkout@v2
+
+      - name: Set up Python 3.9
+        uses: actions/setup-python@v2
+        with:
+          python-version: 3.9
+
+      - name: Install docs dependencies
+        run: |
+          python -m pip install --upgrade pip
+          python -m pip install -r docs/requirements.txt
+
+      - name: Deploy docs
+        uses: mhausenblas/mkdocs-deploy-gh-pages@master
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          CONFIG_FILE: mkdocs.yml
+          REQUIREMENTS: docs/requirements.txt

docs/README.md

@@ -2,6 +2,10 @@
 
 [Back to Fluid Numerics](https://www.fluidnumerics.com)
 
+## [Maximizing Performance, Minimizing Costs: Energy Savings from GPU Optimization](saving-energy-on-quantum-chromodynamics-simulations/README.md)
+![Final performance tables](emprism-mentored-sprint-report/img/image40.png){ align=left width="25%" } 
+In high-performance computing, optimizing GPU workloads isn’t just about speed—it’s about unlocking hidden savings in energy and sustainability. Discover how a 1.91x performance boost turned into real cost savings and why software optimization could transform your operations. [*Read more*](saving-energy-on-quantum-chromodynamics-simulations/README.md)
+
 ## [HIP Performance Comparisons : AMD and Nvidia GPUs](hip-performance-comparisons-amd-and-nvidia-gpus/README.md)
 ![Spectral Element Mesh](hip-performance-comparisons-amd-and-nvidia-gpus/spectral-element-mesh.png){ align=left width="25%" } 
 If you've read some of my other posts, you're aware I'm in the midst of refactoring and updating/upgrade SELF-Fluids. On the upgrade list, I'm planning a swap-out of the CUDA-Fortran implementation for HIP-Fortran, which will allow SELF-Fluids to run on both AMD and Nvidia GPU platforms. This journal entry details a portion of the work I've been doing to understand how some of the core routines in SELF-Fluids will perform across GPU platforms with HIP. [*Read more*](hip-performance-comparisons-amd-and-nvidia-gpus/README.md)