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Related papers: Matrix Distributed Processing and FermiQCD

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Matrix Distributed Processing (MDP) is a C++ library for fast development of efficient parallel algorithms. It constitues the core of FermiQCD. MDP enables programmers to focus on algorithms, while parallelization is dealt with…

High Energy Physics - Lattice · Physics 2007-05-23 Massimo Di Pierro

We present here the most recent version of FermiQCD, a collection of C++ classes, functions and parallel algorithms for lattice QCD, based on Matrix Distributed Processing. FermiQCD allows fast development of parallel lattice applications…

High Energy Physics - Lattice · Physics 2015-06-25 Massimo Di Pierro

We present a set of programming tools (classes and functions written in C++ and based on Message Passing Interface) for fast development of generic parallel (and non-parallel) lattice simulations. They are collectively called MDP 1.2. These…

High Energy Physics - Lattice · Physics 2009-10-31 Massimo Di Pierro

We present Matrix Distributed Processing, a C++ library for fast development of efficient parallel algorithms. MDP is based on MPI and consists of a collection of C++ classes and functions such as lattice, site and field. Once an algorithm…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 Massimo Di Pierro

A quick review of the features of FermiQCD, a C++ library for fast development of parallel Lattice QCD applications. FermiQCD is fully Object Oriented and is based on MPI but, it required no previsius knowledge of parallel programming. It…

FermiQCD is a C++ library for fast development of parallel Lattice Quantum Field Theory computations. It has been developed following a top-down fully Object Oriented design approach with focus on simplicity of use. FermiQCD includes: a…

High Energy Physics - Lattice · Physics 2011-04-11 Massimo Di Pierro , Jonthan M. Flynn

This is a manual (built by examples) to explain the use of MDP_QCD. It consists of an ensemble of classes and functions (written in GNU C++) to help in writing programs for lattice QCD in a particularly Object Oriented fashion. Some tricks…

High Energy Physics - Lattice · Physics 2007-05-23 Massimo Di Pierro

latfield2 is a C++ library designed to simplify writing parallel codes for solving partial differen- tial equations, developed for application to classical field theories in particle physics and cosmology. It is a significant rewrite of the…

Computational Physics · Physics 2016-01-20 David Daverio , Mark Hindmarsh , Neil Bevis

ZKCM is a C++ library developed for the purpose of multiprecision matrix computation, on the basis of the GNU MP and MPFR libraries. It provides an easy-to-use syntax and convenient functions for matrix manipulations including those often…

Mathematical Software · Computer Science 2013-05-14 Akira SaiToh

QCDLAB is a set of programs, written in GNU Octave, for lattice QCD computations. Version 2.0 includes the generation of configurations for the SU(3) theory, computation of rectangle Wilson loops as well as the low lying meson spectrum with…

High Energy Physics - Lattice · Physics 2019-04-22 Artan Borici

We review the architecture of massively parallel machines used for lattice QCD simulations and present benchmarks for the performance of popular algorithms on these platforms. We cover commercial supercomputers, PC clusters, and…

High Energy Physics - Lattice · Physics 2016-09-01 Tilo Wettig

PLQCD is a stand-alone software library developed under PRACE for lattice QCD. It provides an implementation of the Dirac operator for Wilson type fermions and few efficient linear solvers. The library is optimized for multi-core machines…

High Energy Physics - Lattice · Physics 2014-05-06 A. Abdel-Rehim , C. Alexandrou , N. Anastopoulos , G. Koutsou , I. Liabotis , N. Papadopoulou

We present $\texttt{SIMULATeQCD}$, HotQCD's software for performing lattice QCD calculations on GPUs. Started in late 2017 and intended as a full replacement of the previous single GPU lattice QCD code used by the HotQCD collaboration, our…

Current PC processors are equipped with vector processing units and have other advanced features that can be used to accelerate lattice QCD programs. Clusters of PCs with a high-bandwidth network thus become powerful and cost-effective…

High Energy Physics - Lattice · Physics 2007-05-23 Martin Lüscher

Existing distributed machine learning (DML) systems focus on improving the computational efficiency of distributed learning, whereas communication aspects have received less attention. Many DML systems treat the network as a blackbox. Thus,…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-07-02 Raajay Viswanathan , Aditya Akella

We discuss a machine learning (ML) regression model to reduce the computational cost of disconnected diagrams in lattice QCD calculations. This method creates a mapping between the results of fermionic loops computed at different quark…

High Energy Physics - Lattice · Physics 2024-09-02 Jangho Kim , Giovanni Pederiva , Andrea Shindler

mc4qcd is a web based collaboration tool for analysis of Lattice QCD data. Lattice QCD computations consists of a large scale Markov Chain Monte Carlo. Multiple measurements are performed at each MC step. Our system acquires the data by…

High Energy Physics - Lattice · Physics 2011-04-20 Massimo Di Pierro , Yaoqian Zhong , Brian Schinazi

This paper introduces QCDLAB, a design and research tool for lattice QCD algorithms. The tool, a collection of MATLAB functions, is based on a ``small-code'' and a ``minutes-run-time'' algorithmic design philosophy. The present version uses…

High Energy Physics - Lattice · Physics 2007-05-23 Artan Borici

We report on our implementation of LatticeQCD applications using OpenCL. We focus on the general concept and on distributing different parts on hybrid systems, consisting of both CPUs (Central Processing Units) and GPUs (Graphic Processing…

High Energy Physics - Lattice · Physics 2011-12-23 Matthias Bach , Owe Philipsen , Christopher Pinke , Christian Schäfer , Lars Zeidlewicz

Matrix multiplication is the bedrock in Deep Learning inference application. When it comes to hardware acceleration on edge computing devices, matrix multiplication often takes up a great majority of the time. To achieve better performance…

Machine Learning · Computer Science 2021-10-12 Yuyang Zhang , Dik Hin Leung , Min Guo , Yijia Xiao , Haoyue Liu , Yunfei Li , Jiyuan Zhang , Guan Wang , Zhen Chen
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