Early June news batch

_posts/2024-05-18-ddnmrom-new.md

@@ -0,0 +1,6 @@
+---
+title: "New Repo: DD-NM-ROM"
+categories: new-repo
+---
+
+[DD-NM-ROM](https://github.com/LLNL/DD-NM-ROM) integrates nonlinear-manifold reduced order models (NM-ROMs) with domain decomposition (DD). NM-ROMs approximate the full order model (FOM) state in a nonlinear-manifold by training a shallow, sparse autoencoder using FOM snapshot data. The code implementation was done using Python 3.9 and a CUDA-11.4 environment.

_posts/2024-05-21-gwap-new.md

@@ -0,0 +1,6 @@
+---
+title: "New Repo: GWAP"
+categories: new-repo
+---
+
+Ground Water Age Predictor ([GWAP](https://github.com/LLNL/GWAP)): Groundwater ages provide insight into recharge rates, flow velocities, and vulnerability to contaminants. The ability to predict groundwater ages based on more accessible parameters via machine learning (ML) would advance our ability to guide sustainable management of groundwater resources. In this work, ML models were trained and tested on a large dataset of tritium concentrations (n=2410) and tritium-helium groundwater ages (n=1157) from the California Central Valley, a large groundwater basin with complex land use, irrigation, and water management practices. The dataset collected by the California Waterboards for the Groundwater Ambient Monitoring and Assessment (GAMA) program and can be [downloaded](https://gamagroundwater.waterboards.ca.gov/gama/gamamap/public/).

_posts/2024-05-24-surfactant.md

@@ -0,0 +1,6 @@
+---
+title: "Video: Surfactant at Black Hat Asia Arsenal"
+categories: event multimedia
+---
+
+[Surfactant](https://github.com/LLNL/surfactant) is a modular framework for extracting information from file systems, primarily for generating an SBOM (Software Bill of Materials). The information extracted can then be used to identify the various vendors or libraries associated with a file and establish relationships between files. The resulting SBOM can be used for system level impact analysis (e.g., for IoT, Smart Grid, ICS devices) of vulnerabilities, and the information gathered can be used to help inform what files to focus on for manual analysis. In [this video from Black Hat Asia Arsenal](https://www.youtube.com/watch?v=O7ONPNz9jyw), LLNL's cyber security software engineer Ryan Mast demonstrates how to use Surfactant to create SBOMs. The video's runtime is 20:15.

_posts/2024-05-31-thousand.md

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+---
+title: "The Lab That Launched a Thousand Software Projects"
+categories: story
+---
+
+Thanks to a dynamic developer community and a long history of encouraging open-source software development, Lawrence Livermore has reached quadruple-digit GitHub offerings. One thousand—and counting!—LLNL software projects have been publicly released on the GitHub platform since the first one was published in October 2008. These projects address a wide range of needs: software tailored for unique high performance computing scenarios, user documentation, tutorials, automation tools, scientific applications, student projects, codes accompanying research papers, and much more. Some have been in development for decades, while others serve a single ephemeral purpose. [Read more at LLNL Computing.](https://computing.llnl.gov/about/newsroom/lab-launched-thousand-software-projects)

_typos.toml

@@ -3,6 +3,7 @@ BA = "BA"
 Cleary = "Cleary"
 compsite = "compsite"
 epsiode = "epsiode"
+FOM = "FOM"
 NED = "NED"
 SUite = "SUite"
 Universite = "Universite"