![alkemi the word on a green background](/sites/default/files/styles/front_page_card/public/alkemi-llnl-project-card.png?itok=G7Fvrm6N)
Alkemi
Simulation workflows for ALE methods often require a manual tuning process. We are developing novel predictive analytics for simulations and an infrastructure for integration of analytics.
![AIMS logo overlaid on image of the earth](/sites/default/files/styles/front_page_card/public/aims-llnl-project-card.png?itok=iTtkz66w)
AIMS
AIMS (Analytics and Informatics Management Systems) develops integrated cyberinfrastructure for big climate data discovery, analytics, simulations, and knowledge innovation.
![simulation of mountainous terrain](/sites/default/files/styles/front_page_card/public/soar-llnl-project-card.png?itok=WSjkBaeR)
SOAR
SOAR (Stateless, One-pass Adaptive Refinement) is a view-dependent mesh refinement and rendering algorithm.
![Top row: two photos of a large building with a spire corrupted by glass blur and shot noise; bottom row: two multicolored rectangles (spectral heatmaps) corresponding to the photos](/sites/default/files/styles/front_page_card/public/2023-12/Comp-NIC-news-leaderboard.png?itok=dbUQn7H1)
Conference paper illuminates neural image compression
New research reveals subtleties in the performance of neural image compression methods, offering insights toward improving these models for real-world applications.
![LLNL software developer Kristi Belcher discusses a poster with attendees at the SC23 Poster Session](/sites/default/files/styles/front_page_card/public/2023-11/sc23-kristi-comp.png?itok=a2TvHgxC)
Record-setting SC23 builds mile-high momentum for exascale computing, AI, and the future of HPC
A record number of attendees—more than 14,000—experts, researchers, vendors and enthusiasts in the field of HPC descended on the Mile High City for the 2023 International Conference for High Performance Computing, Networking, Storage and Analysis, colloquially known as SC23.
![x-ray image showing the interior of a piece of luggage](/sites/default/files/styles/front_page_card/public/2023-11/dolce-comp-leaderboard.png?itok=SRy8jcHz)
For better CT images, new deep learning tool helps fill in the blanks
LLNL researchers collaborated with Washington University in St. Louis to devise a state-of-the-art ML–based reconstruction tool for when high-quality computed tomography data is in low supply.