Topic: Open-Source Software

This project solves initial value problems for ODE systems, sensitivity analysis capabilities, additive Runge-Kutta methods, DAE systems, and nonlinear algebraic systems.

The open-source MFEM library enables application scientists to quickly prototype parallel physics application codes based on PDEs discretized with high-order finite elements.

Highlights include ML techniques for computed tomography, a scalable Gaussian process framework, safe and trustworthy AI, and autonomous multiscale simulations.

Todd Gamblin has a well-deserved reputation in the HPC software community as a passionate engineer who enjoys rolling up his sleeves and diving into technical problems. It’s not a stretch to see how he got hooked on HPC.

Presented last fall at a conference, a new approach to software binary analysis incorporates large-scale training data and hierarchical embeddings.

Two teams led by LLNL computer scientists won Editor’s Awards from HPCwire, a leading high performance computing industry publication, at the 2024 Supercomputing Conference in Atlanta.

Held for the first time in a hybrid format, the multi-day MFEM workshop drew participants from around the globe.

An iconic LLNL computer code that has saved the automobile industry billions of dollars is the focus for the newest episode of the Big Ideas Lab Podcast.

The latest issue of R&D World's magazine showcases LLNL's 2024 winning technologies, including UnifyFS and UMap software projects.

LLNL is participating in the 36th annual Supercomputing Conference (SC24) in Atlanta on November 17–22, 2024.

AMS is a machine learning solution embedded into scientific applications to automatically replace fine-scale simulations with ancillary models.

Follow along at your own pace through tutorials of several open-source HPC software projects.

Specialized hardware modules and software libraries to optimize memory access while simultaneously increasing memory capacity for data-intensive applications.

An optics element team and two open-source software teams (UMap and UnifyFS) are LLNL's winners of this year's awards.

This issue highlights some of CASC’s contributions to the DOE's Exascale Computing Project.

Bugs, broken codes, or system failures require added time for troubleshooting and increase the risk of data loss. LLNL has addressed failure recovery by developing the Scalable Checkpoint/Restart (SCR) framework.

With SCR, jobs run more efficiently, recover more work upon failure, and reduce load on critical shared resources.

Collecting variants in low-level hardware features across multiple GPU and CPU architectures.

LLNL’s HPC capabilities play a significant role in international science research and innovation, and Lab researchers have won 10 R&D 100 Awards in the Software–Services category in the past decade.

zfp is an open-source C/C++ library for compressed floating-point and integer arrays that support high throughput read and write random access.

Two LLNL teams have come up with ingenious solutions to a few of the more vexing difficulties. For their efforts, they’ve won awards coveted by scientists in the technology fields.

Release the codes! With a dynamic developer community and a long history of encouraging open-source software, LLNL has reached quadruple-digit GitHub offerings.

Learn how to use a modern, open-source HPC software stack! Throughout August, join our tutorials on how to install and use several projects on AWS EC2 instances. No previous experience is necessary, and everyone is welcome.

UMap uniquely exploits the prominent role of complex memories in today’s servers and offers new capabilities to directly access large memory-mapped datasets.

This open-source file system framework accelerates hierarchical HPC I/O operations with effective, efficient use of node-local storage.