SANTA CLARA — AMD showcased its high performance computing (HPC) leadership at Supercomputing 2024 by powering the world’s fastest supercomputer for the sixth straight Top500 list.
The El Capitan supercomputer, housed at Lawrence Livermore National Laboratory (LLNL), powered by AMD Instinct MI300A APUs and built by Hewlett Packard Enterprise (HPE), is now the fastest supercomputer in the world with a High-Performance Linpack (HPL) score of 1.742 exaflops based on the latest Top500 list. Both El Capitan and the Frontier system at Oak Ridge National Lab claimed numbers 18 and 22, respectively, on the Green500 list, showcasing the impressive capabilities of the AMD EPYC processors and AMD Instinct GPUs to drive leadership performance and energy efficiency for HPC workloads.
“We are thrilled to see El Capitan become the second AMD powered supercomputer to break the exaflop barrier and become the fastest supercomputer in the world. Showcasing the incredible performance and efficiency of the AMD Instinct MI300 APUs, this groundbreaking machine is a testament to the dedicated work between AMD, LLNL and HPE,” said Forrest Norrod, executive vice president and general manager, AMD. “At AMD, we are driving the future of computing with leadership performance and capabilities that will continue to define the convergence of HPC and AI for years to come.”
“El Capitan is crucial to the National Nuclear Security Administration’s core mission and significantly bolsters our ability to perform large ensembles of high-fidelity 3D simulations that address the intricate scientific challenges facing the mission,” said Rob Neely, director of LLNL’s Advanced Simulation and Computing program.
Bronis R. de Supinski, LLNL’s chief technology officer for Livermore Computing adds, “Leveraging the AMD Instinct MI300A APUs, we’ve built a system that was once unimaginable, pushing the absolute boundaries of computational performance while maintaining exceptional energy efficiency. With AI becoming increasingly prevalent in our field, El Capitan allows us to integrate AI with our traditional simulation and modeling workloads, opening new avenues for discovery across various scientific disciplines.”
