
Explore the dawn of exascale computing, focusing on the Frontier system, its applications, and the challenges overcome in developing exascale-capable software and technologies.

Explore the rapid deployment and sustainability of Isambard-AI, a national Exascale AI research resource in the UK, including its architecture, applications, and impact on AI research.

Explore LLNL's open-source HPC software portfolio and learn about collaboration opportunities in the exascale era. Gain insights into innovative tools addressing emerging challenges in high-performance computing.

Explore exascale computing, HPC architectures, and GPU programming with Dr. Meifeng Lin from Brookhaven National Laboratory.

Explore the Template Task Graph programming paradigm for expressing task parallelism in algorithms with irregular data sets. Learn installation and integration techniques.

Explore code review benefits for scientific software: improved quality, teamwork, and knowledge transfer. Learn approaches to facilitate effective reviews.

Explore lab notebooks' adaptation to computational research, with examples addressing challenges in transitioning from experimental to computational sciences.

Explore the journey to exascale computing in particle accelerator and laser-plasma modeling, featuring WarpX's development and the 2022 ACM Gordon Bell Prize.

Explore GPU-based electronic structure computations for exascale platforms using PROGRESS and BML libraries. Learn implementation strategies, performance optimization, and scaling techniques.

Explore infrastructure and tools for high-fidelity testing in HPC environments, focusing on hardening software for DOE's Exascale Computing Project and future applications.

Explore secure software development practices to mitigate malicious attacks and protect scientific software integrity, authentication, and sustainability.

Explore exascale computing advancements, best practices, and future trends in high-performance computing. Learn strategies for developing portable, performant code and adapting algorithms for heterogeneous architectures.

Explore innovative solutions for HPC and AI bottlenecks through Memory Coupled Compute architecture, addressing bandwidth limitations and accelerator efficiency for post-exascale computing.