LLNL Computing’s ground-breaking research and development activities, innovative technologies, and world-class staff are often featured in various media outlets.

Simulated strength of shaking from a magnitude 7.0 Hayward Fault earthquake showing peak ground velocity (colorbar) and seismograms (blue) at selected locations (triangles)

Source: LLNL News

Lab team completes highest-ever resolution quake simulations using Sierra

An LLNL team has published new simulations of a magnitude 7.0 earthquake on the Hayward Fault—the highest-ever resolution ground motion simulations from such an event on this scale.

Computational Science | Seismology

simulation of arterial blood flow using HARVEY

Source: LLNL News

Using models, 3D printing to study common heart defect

LLNL researchers and collaborators have combined machine learning, 3D printing, and HPC simulations to accurately model blood flow in the aorta.

Biology/Biomedicine | Computational Science

SCR team in front of Sierra with R&D 100 logo

Source: Science & Technology Review

Resiliency in computer applications

In this issue featuring LLNL's R&D 100 Award winners from 2019, the versatile Scalable Checkpoint/Restart framework offers more reliable simulation performance.

Awards | Fault Tolerance and Resilience | HPC Systems and Software | Open-Source Software

Spack team in B453 lobby with R&D 100 logo

Source: Science & Technology Review

Software installation simplified

In this issue featuring LLNL's R&D 100 Award winners from 2019, software deployment is faster and easier with the Spack package management tool.

Awards | HPC Systems and Software | Open-Source Software | Software Build and Installation

Screen shot of video showing the DSI logo over an aerial view of the Lab

Source: YouTube.com

Video: Advancing healthcare with data science

This video provides an overview of LLNL projects in which data scientists work with domain scientists to address major challenges in healthcare.

Biology/Biomedicine | Computational Science | Data Science | Multimedia

Screenshot of Ian being interviewed

Source: Next Platform TV

AI acceleration: a Next Platform TV interview

Ian Karlin on AI hardware integration into HPC systems, workflows, followed by a talk about software integration of AI accelerators in HPC with Brian Van Essen.

AI/ML | Data Science | HPC Systems and Software

diagram of a new “Mix-n-Match” method for calibrating uncertainty of deep learning models

Source: LLNL News

LLNL papers accepted into prestigious conference

Two papers featuring LLNL scientists were accepted in the 2020 International Conference on Machine Learning (ICML), one of the world’s premier conferences of its kind.

AI/ML | Data Science | Deep Learning | Events | ML Theory

model of a molecule next to a screen shot of webex meeting participants in video chat

Source: LLNL News

Lockdown doesn’t hinder annual Data Science Challenge

In this year's Data Science Challenge with UC Merced, 21 students developed machine learning models capable of differentiating potentially explosive materials from other types of molecules.

Data Science | Students

screen shot of finite element method animation from the video

Source: YouTube.com

Video: MFEM - advanced simulation algorithms for HPC applications

This video describes MFEM (Modular Finite Element Methods), an open-source software library that provides advanced mathematical algorithms for use by scientific applications.

Computational Math | Discrete Mathematics | Multimedia | Open-Source Software

drawing of a reactor tube

Source: LLNL News

Manufacturing, Energy Initiative to fund 11 new projects

In the HPC4EI project, LLNL and OxEon Energy will reduce the number of reactor tubes used to convert natural gas to liquid fuel, to lower cost and increase performance of synthetic fuel production.

Computational Science | Hydrodynamics

drawing of the Exascale Computing Facility

Source: LLNL News

Lab breaks ground for exascale facility upgrades

Scheduled for completion in 2022, the project will expand the Livermore Computing Center's power and cooling capacity in preparation for exascale supercomputing hardware.

HPC Architectures | HPC Systems and Software

Sierra supercomputer and National Ignition Facility photos combined with abstract graphic representing experimental data and simulations

Source: LLNL News

Deep learning models outperform simulators, could hasten scientific discoveries

Surrogate models supported by neural networks could lead to new insights in complicated physics problems such as inertial confinement fusion.

Computational Science | Data Science | Deep Learning | Scientific ML

two people conduct RFI scanning in a supply cabinet

Source: LLNL Computing

Computing partners with environmental programs at the Lab

Computing employees play a critical role in supporting the Environmental Restoration Department; Environment, Safety, and Health; and Radioactive and Hazardous Waste Management.

Business Applications and Support | Information Technology

Sierra supercomputer with text overlay of ISC logo

Source: LLNL Computing

ISC20 event calendar

LLNL participates in the digital ISC High Performance Conference (ISC20) on June 22 to 25.

Events | HPC Systems and Software

MFEM logo

Source: Exascale Computing Project

Podcast: The MFEM finite element library broadens GPU support

The Center for Efficient Exascale Discretizations recently released MFEM v4.1, which introduces features important for the nation’s first exascale supercomputers. LLNL's Tzanio Kolev explains.

Computational Math | Discrete Mathematics | HPC Systems and Software | Hybrid/Heterogeneous | Multimedia | Open-Source Software

Magma supercomputer

Source: The Next Platform

Cooling Magma is a challenge that Lawrence Livermore can take on

LLNL's latest HPC system, aptly nicknamed “Magma," delivers 5.4 petaflops of peak performance crammed into 760 compute nodes.

HPC Architectures | HPC Systems and Software

series of images depicting the progression of a patient (current state) diagnosed with COVID-19

Source: LLNL News

Lab team studies AI and DL models to reliably diagnose and treat disease

An LLNL-led team proposes a DL approach aimed at improving the reliability of classifier models for predicting disease types from diagnostic images.

AI/ML | Biology/Biomedicine | Computational Science | Data Science | Deep Learning | ML Theory

topological analysis of X-ray CT data for recognition and trending of changes in microstructure under material aging

Source: LLNL News

AI identifies change in microstructure in aging materials

LLNL scientists have taken a step forward in the design of future materials with improved performance by analyzing its microstructure using artificial intelligence.

AI/ML | Computational Science | Data Science | Materials Science

protein structures of SARS-CoV-2

Source: LLNL News

COVID-19 research goes public through new portal

To help accelerate discovery of therapeutic antibodies or antiviral drugs for SARS-CoV-2, LLNL has launched a searchable data portal to share its COVID-19 research with scientists and the public.

Biology/Biomedicine | Computational Science | Data Management | Data Science | Information Technology | Software Engineering | Web Technologies

data skeptic podcast logo

Source: Data Skeptic

Podcast: Interpretable AI in healthcare

LLNL's Jay Thiagarajan joins the Data Skeptic podcast to discuss his recent paper "Calibrating Healthcare AI: Towards Reliable and Interpretable Deep Predictive Models." The episode runs 35:50.

AI/ML | Biology/Biomedicine | Computational Science | Data Science | ML Theory | Multimedia

people video chatting with an image of a cursor arrow on a computer screen

Source: Better Scientific Software

Working remotely: the Spack team

Elaine Raybourn interviews LLNL's Todd Gamblin about the Spack project's experience working remotely.

HPC Systems and Software | Open-Source Software | Software Build and Installation

simulation showing a laser interacting simultaneously with the melt pool and a large “spatter” of metal powder particle

Source: LLNL News

Lab devises plan to reduce defects in 3D metal printing

Combining computer simulations with ultra-high-speed X-ray imaging, LLNL researchers have discovered a way to reduce defects in parts built through a laser-based metal 3D-printing process.

Computational Science | Materials Science

screen shot of the first slide in the deck

Source: insideHPC

Video: Incorporation of machine learning into scientific simulations at LLNL

In this video from the Stanford HPC Conference, Katie Lewis presents "The Incorporation of Machine Learning into Scientific Simulations at Lawrence Livermore National Laboratory."

AI/ML | Computational Science | Data Science | Multimedia | Scientific ML

abstract design showing layers of materials and chemicals on a stylized background

Source: Data Science Institute

Building knowledge and insights using machine learning of scientific articles

An LLNL team developed ML tools that extract and structure information from the text and figures of nanomaterials articles using NLP, image analysis, computer vision, and visualization techniques.

AI/ML | Computational Science | Data Science | Data-Driven Decisions | Materials Science