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We present the first open release of the DCA++ project, a high-performance research software framework to solve quantum many-body problems with cutting edge quantum cluster algorithms. DCA++ implements the dynamical cluster approximation…

The use of quantum processing units (QPUs) promises speed-ups for solving computational problems. Yet, current devices are limited by the number of qubits and suffer from significant imperfections, which prevents achieving quantum…

Quantum Physics · Physics 2023-06-08 Hila Safi , Karen Wintersperger , Wolfgang Mauerer

Graphics Processing Units (GPUs) support dynamic voltage and frequency scaling (DVFS) in order to balance computational performance and energy consumption. However, there still lacks simple and accurate performance estimation of a given GPU…

Performance · Computer Science 2018-06-14 Qiang Wang , Xiaowen Chu

In recent years, it has become increasingly common for high performance computers (HPC) to possess some level of heterogeneous architecture - typically in the form of GPU accelerators. In some machines these are isolated within a dedicated…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-10-19 I. Zacharoudiou , J. W. S. McCullough , P. V. Coveney

A previous case study measured performance vs source-code complexity across multiple languages. The case study identified Chapel and HPX provide similar performance and code complexity. This paper is the result of initial steps toward…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-11-26 Shreyas Atre , Chris Taylor , Patrick Diehl , Hartmut Kaiser

Graphics processing units (GPU) had evolved from a specialized hardware capable to render high quality graphics in games to a commodity hardware for effective processing blocks of data in a parallel schema. This evolution is particularly…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-03-26 Luis Cabellos

An increasingly large number of HPC systems rely on heterogeneous architectures combining traditional multi-core CPUs with power efficient accelerators. Designing efficient applications for these systems has been troublesome in the past as…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-03-02 E. Calore , A. Gabbana , J. Kraus , S. F. Schifano , R. Tripiccione

General-purpose Computing on Graphics Processing Units (GPGPU) has been introduced to many areas of scientific research such as bioinformatics, cryptography, computer vision, and deep learning. However, computing models in the High-energy…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-07-23 Max Isacson , Mattias Ellert , Richard Brenner

Interest in many-core architectures applied to real time selections is growing in High Energy Physics (HEP) experiments. In this paper we describe performance measurements of many-core devices when applied to a typical HEP online task: the…

Instrumentation and Detectors · Physics 2014-11-25 A. Gianelle , S. Amerio , D. Bastieri , M. Corvo , W. Ketchum , T. Liu , A. Lonardo , D. Lucchesi , S. Poprocki , R. Rivera , L. Tosoratto , P. Vicini , P. Wittich

The ongoing convergence of HPC and cloud computing presents a fundamental challenge: HPC applications, designed for static and homogeneous supercomputers, are ill-suited for the dynamic, heterogeneous, and volatile nature of the cloud.…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-03-17 Aditya Bhosale , Advait Tahilyani , Laxmikant Kale , Sara Kokkila-Schumacher

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…

In this work, we consider the reformulation of hierarchical ($\mathcal{H}$) matrix algorithms for many-core processors with a model implementation on graphics processing units (GPUs). $\mathcal{H}$ matrices approximate specific dense…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-09-04 Peter Zaspel

In this work we evaluate the potential of FPGAs for accelerating HPC workloads as a more power-efficient alternative to GPUs. Using High-Level Synthesis and a large set of optimization techniques, we show that FPGAs can achieve better…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-09-17 Hamid Reza Zohouri

With rapidly evolving technology, multicore and manycore processors have emerged as promising architectures to benefit from increasing transistor numbers. The transition towards these parallel architectures makes today an exciting time to…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-04-01 Ashkan Tousimojarad , Wim Vanderbauwhede

Parallel algorithms relying on synchronous parallelization libraries often experience adverse performance due to global synchronization barriers. Asynchronous many-task runtimes offer task futurization capabilities that minimize or remove…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-06-05 Alexander Strack , Christopher Taylor , Patrick Diehl , Dirk Pflüger

In this paper we deal with the impact of multi and many-core processor architectures on simulation. Despite the fact that modern CPUs have an increasingly large number of cores, most softwares are still unable to take advantage of them. In…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-07-30 Gabriele D'Angelo , Stefano Ferretti , Moreno Marzolla

The Simplex tableau has been broadly used and investigated in the industry and academia. With the advent of the big data era, ever larger problems are posed to be solved in ever larger machines whose architecture type did not exist in the…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-05-29 Demetrios Coutinho , Felipe O. Lins e Silva , Daniel Aloise , Samuel , Xavier-de-Souza

In this paper, we analyze the performance and energy consumption of an Arm-based high-performance computing (HPC) system developed within the European project Mont-Blanc 3. This system, called Dibona, has been integrated by ATOS/Bull, and…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-07-13 Filippo Mantovani , Marta Garcia-Gasulla , José Gracia , Esteban Stafford , Fabio Banchelli , Marc Josep-Fabrego , Joel Criado-Ledesma , Mathias Nachtmann

Multi-core architectures feature an intricate hierarchy of cache memories, with multiple levels and sizes. To adequately decompose an application according to the traits of a particular memory hierarchy is a cumbersome task that may be…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-11-20 Hervé Paulino , Nuno Delgado

A current trend in HPC systems is the utilization of architectures with SIMD or vector extensions to exploit data parallelism. There are several ways to take advantage of such modern vector architectures, each with a different impact on the…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-11-05 Marc Blancafort , Roger Ferrer , Guillaume Houzeaux , Marta Garcia-Gasulla , Filippo Mantovani