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SISSO (sure-independence screening and sparsifying operator) is an artificial intelligence (AI) method based on symbolic regression and compressed sensing widely used in materials science research. SISSO++ is its C++ implementation that…

Performance · Computer Science 2025-02-28 Sebastian Eibl , Yi Yao , Matthias Scheffler , Markus Rampp , Luca M. Ghiringhelli , Thomas A. R. Purcell

The development of the A64FX processor by Fujitsu has been a massive innovation in vectorized processors and led to Fugaku: the current world's fastest supercomputer. We use a variety of tools to analyze the behavior and performance of…

Performance · Computer Science 2021-06-21 Benjamin Michalowicz , Eric Raut , Yan Kang , Tony Curtis , Barbara Chapman , Dossay Oryspayev

A heterogeneous CPU-GPU node is getting popular in HPC clusters. We need to rethink algorithms and optimization techniques for such system depending on the relative performance of CPU vs. GPU. In this paper, we report a performance…

Instrumentation and Methods for Astrophysics · Physics 2012-06-07 Naohito Nakasato , Go Ogiya , Yohei Miki , Masao Mori , Ken'ichi Nomoto

To achieve scalability with today's heterogeneous HPC resources, we need a dramatic shift in our thinking; MPI+X is not enough. Asynchronous Many Task (AMT) runtime systems break down the global barriers imposed by the Bulk Synchronous…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-01-09 Thomas Heller , Patrick Diehl , Zachary Byerly , John Biddiscombe , Hartmut Kaiser

Scientific computing in the exascale era demands increased computational power to solve complex problems across various domains. With the rise of heterogeneous computing architectures the need for vendor-agnostic, performance portability…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-11-05 Johansell Villalobos , Josef Ruzicka , Silvio Rizzi

Analyzing performance within asynchronous many-task-based runtime systems is challenging because millions of tasks are launched concurrently. Especially for long-term runs the amount of data collected becomes overwhelming. We study HPX and…

The A64FX processor from Fujitsu, being designed for computational simulation and machine learning applications, has the potential for unprecedented performance in HPC systems. In this paper, we evaluate the A64FX by benchmarking against a…

Performance · Computer Science 2020-09-25 Adrian Jackson , Michèle Weiland , Nick Brown , Andrew Turner , Mark Parsons

We explore the performance and portability of the high-level programming models: the LLVM-based Julia and Python/Numba, and Kokkos on high-performance computing (HPC) nodes: AMD Epyc CPUs and MI250X graphical processing units (GPUs) on…

Portability is critical to ensuring high productivity in developing and maintaining scientific software as the diversity in on-node hardware architectures increases. While several programming models provide portability for diverse GPU…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-09-08 Joshua H. Davis , Pranav Sivaraman , Joy Kitson , Konstantinos Parasyris , Harshitha Menon , Isaac Minn , Giorgis Georgakoudis , Abhinav Bhatele

Next generation High-Energy Physics (HEP) experiments are presented with significant computational challenges, both in terms of data volume and processing power. Using compute accelerators, such as GPUs, is one of the promising ways to…

This paper describes how we successfully used the HPX programming model to port the DCA++ application on multiple architectures that include POWER9, x86, ARM v8, and NVIDIA GPUs. We describe the lessons we can learn from this experience as…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-21 Weile Wei , Arghya Chatterjee , Kevin Huck , Oscar Hernandez , Hartmut Kaiser

NVIDIA has been the main provider of GPU hardware in HPC systems for over a decade. Most applications that benefit from GPUs have thus been developed and optimized for the NVIDIA software stack. Recent exascale HPC systems are, however,…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-09-12 Igor Sfiligoi , Emily A. Belli , Jeff Candy , Reuben D. Budiardja

We present an expanded study of the performance of FLASH when using Linux Kernel Hugepages on Ookami, an HPE Apollo 80 A64FX platform. FLASH is a multi-scale, multi-physics simulation code written principally in modern Fortran and makes use…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-09-19 Catherine Feldman , Smeet Chheda , Alan C. Calder , Eva Siegmann , John Dey , Tony Curtis , Robert J. Harrison

The current number one of the TOP500 list, Supercomputer Fugaku, has demonstrated that CPU-only HPC systems aren't dead and CPUs can be used for more than just being the host controller for a discrete accelerators. While the specifications…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-08-03 Jens Domke

Experience shows that on today's high performance systems the utilization of different acceleration cards in conjunction with a high utilization of all other parts of the system is difficult. Future architectures, like exascale clusters,…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-03-07 Patrick Diehl , Madhavan Seshadri , Thomas Heller , Hartmut Kaiser

Quantum computer simulators running on classical computers are essential for developing real quantum computers and emerging quantum applications. In particular, state vector simulators, which store a full state vector in memory and update…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-03-31 Satoshi Imamura , Masafumi Yamazaki , Takumi Honda , Akihiko Kasagi , Akihiro Tabuchi , Hiroshi Nakao , Naoto Fukumoto , Kohta Nakashima

The nonuniform fast Fourier transform (NUFFT) enables spectral methods for problems with irregularly spaced samples, with applications in medical imaging, molecular dynamics, and kinetic plasma simulations. Existing implementations are…

Computational Engineering, Finance, and Science · Computer Science 2026-05-12 Paul Fischill , Andreas Adelmann , Sriramkrishnan Muralikrishnan

This paper reports on an in-depth evaluation of the performance portability frameworks Kokkos and RAJA with respect to their suitability for the implementation of complex particle-in-cell (PIC) simulation codes, extending previous studies…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-11-20 Victor Artigues , Katharina Kormann , Markus Rampp , Klaus Reuter

A considerable amount of research and engineering went into designing proxy applications, which represent common high-performance computing workloads, to co-design and evaluate the current generation of supercomputers, e.g., RIKEN's…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-04-18 Satoshi Matsuoka , Jens Domke , Mohamed Wahib , Aleksandr Drozd , Ray Bair , Andrew A. Chien , Jeffrey S. Vetter , John Shalf

Developing parallel algorithms efficiently requires careful management of concurrency across diverse hardware architectures. C++ executors provide a standardized interface that simplifies the development process, allowing developers to…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-22 Karame Mohammadiporshokooh , Steven R. Brandt , Hartmut Kaiser