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QPACE is a novel parallel computer which has been developed to be primarily used for lattice QCD simulations. The compute power is provided by the IBM PowerXCell 8i processor, an enhanced version of the Cell processor that is used in the…

Quantum computers process information with the laws of quantum mechanics. Current quantum hardware is noisy, can only store information for a short time, and is limited to a few quantum bits, i.e., qubits, typically arranged in a planar…

Numerical lattice quantum chromodynamics studies of the strong interaction are important in many aspects of particle and nuclear physics. Such studies require significant computing resources to undertake. A number of proposed methods…

High Energy Physics - Lattice · Physics 2021-04-08 Phiala E. Shanahan , Amalie Trewartha , William Detmold

A quantum computer is a hypothetical device in which the laws of quantum mechanics are used to introduce a degree of parallelism into computations and which could therefore significantly improve on the computational speed of a classical…

Quantum Physics · Physics 2007-05-23 P. Blythe , B. Varcoe

Many appplications in computational science are sufficiently compute-intensive that they depend on the power of parallel computing for viability. For all but the "embarrassingly parallel" problems, the performance depends upon the level of…

High Energy Physics - Lattice · Physics 2009-09-29 Z. Sroczynski , N. Eicker , Th. Lippert , B. Orth , K. Schilling

Using commodity component personal computers based on Alpha processor and commodity network devices and a switch, we built an 8-node parallel computer. GNU/Linux is chosen as an operating system and message passing libraries such as PVM,…

High Energy Physics - Lattice · Physics 2015-06-25 Seyong Kim

Quantum machine learning deals with leveraging quantum theory with classic machine learning algorithms. Current research efforts study the advantages of using quantum mechanics or quantum information theory to accelerate learning time or…

Quantum Physics · Physics 2025-09-03 Javier Orduz , Pablo Rivas , Erich Baker

Rapid advances in quantum computing technology lead to an increasing need for software simulators that enable both algorithm design and the validation of results obtained from quantum hardware. This includes calculations that aim at probing…

Quantum Physics · Physics 2025-01-09 Amit Jamadagni , Andreas M. Läuchli , Cornelius Hempel

The use of graphics processing units for scientific computations is an emerging strategy that can significantly speed up various different algorithms. In this review, we discuss advances made in the field of computational physics, focusing…

Computational Physics · Physics 2013-03-07 Ari Harju , Topi Siro , Filippo Federici-Canova , Samuli Hakala , Teemu Rantalaiho

In these proceedings, we review recent advances in applying quantum computing to lattice field theory. Quantum computing offers the prospect to simulate lattice field theories in parameter regimes that are largely inaccessible with the…

High Energy Physics - Lattice · Physics 2023-08-10 Lena Funcke , Tobias Hartung , Karl Jansen , Stefan Kühn

The implementation of a proof-of-concept Lattice Quantum Chromodynamics kernel on the Cell processor is described in detail, illustrating issues encountered in the porting process. The resulting code performs up to 45GFlop/s per socket,…

High Energy Physics - Lattice · Physics 2008-11-26 J. Spray , J. Hill , A. Trew

QCDOC is a massively parallel supercomputer whose processing nodes are based on an application-specific integrated circuit (ASIC). This ASIC was custom-designed so that crucial lattice QCD kernels achieve an overall sustained performance of…

The L-CSC (Lattice Computer for Scientific Computing) is a general purpose compute cluster built of commodity hardware installed at GSI. Its main operational purpose is Lattice QCD (LQCD) calculations for physics simulations. Quantum Chromo…

Performance · Computer Science 2017-12-29 D. Rohr , G. Neskovic , M. Radtke , V. Lindenstruth

The L-CSC (Lattice Computer for Scientific Computing) is a general purpose compute cluster built with commodity hardware installed at GSI. Its main operational purpose is Lattice QCD (LQCD) calculations for physics simulations. Quantum…

Performance · Computer Science 2018-11-29 David Rohr , Gvozden Neskovic , Volker Lindenstruth

Extensions to the C++ implementation of the QCD Data Parallel Interface are provided enabling acceleration of expression evaluation on NVIDIA GPUs. Single expressions are off-loaded to the device memory and execution domain leveraging the…

High Energy Physics - Lattice · Physics 2011-11-24 Frank Winter

We report on our implementation of the RHMC algorithm for the simulation of lattice QCD with two staggered flavors on Graphics Processing Units, using the NVIDIA CUDA programming language. The main feature of our code is that the GPU is not…

High Energy Physics - Lattice · Physics 2012-01-26 Claudio Bonati , Guido Cossu , Massimo D'Elia , Pietro Incardona

Simulating quantum circuits (QC) on high-performance computing (HPC) systems has become an essential method to benchmark algorithms and probe the potential of large-scale quantum computation despite the limitations of current quantum…

Lattice QCD is progressing toward being able to impact our understanding of nuclei and nuclear processes. I discuss areas of nuclear physics that are becoming possible to explore with lattice QCD, the techniques that are currently available…

High Energy Physics - Lattice · Physics 2007-05-23 Martin J. Savage

We report on the progress of the software effort in the QCD Application Area of SciDAC. In particular, we discuss how the software developed under SciDAC enabled the aggressive exploitation of leadership computers, and we report on progress…

High Energy Physics - Lattice · Physics 2019-08-13 Balint Joo

Neural networks have been successfully applied in various resource-constrained edge devices, where usually central processing units (CPUs) instead of graphics processing units exist due to limited power availability. State-of-the-art…

Machine Learning · Computer Science 2026-01-30 Daniel Stein , Shaoyi Huang , Rolf Drechsler , Bing Li , Grace Li Zhang
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