نتایج جستجو برای: quantum espresso

تعداد نتایج: 296639  

Journal: :Journal of physics. Condensed matter : an Institute of Physics journal 2017
Oliviero Andreussi Thomas Brumme Oana Bunau Marco Buongiorno Nardelli Matteo Calandra Roberto Car Carlo Cavazzoni Davide Ceresoli Matteo Cococcioni Nicola Colonna Ivan Carnimeo Andrea Dal Corso Stefano de Gironcoli Pietro Delugas Robert DiStasio Andrea Ferretti Andrea Floris Guido Fratesi Giorgia Fugallo Ralph Gebauer Uwe Gerstmann Feliciano Giustino Tommaso Gorni Junteng Jia Mitsuaki Kawamura Hsin-Yu Ko Anton Kokalj Emine Küçükbenli Michele Lazzeri Margherita Marsili Nicola Marzari Francesco Mauri Ngoc Linh Nguyen Huy-Viet Nguyen Alberto Otero-de-la-Roza Lorenzo Paulatto Samuel Poncé Paolo Giannozzi Dario Rocca Riccardo Sabatini Biswajit Santra Martin Schlipf Ari Paavo Seitsonen Alexander Smogunov Iurii Timrov Timo Thonhauser Paolo Umari Nathalie Vast Xifan Wu Stefano Baroni

Quantum EXPRESSO is an integrated suite of open-source computer codes for quantum simulations of materials using state-of-the-art electronic-structure techniques, based on density-functional theory, density-functional perturbation theory, and many-body perturbation theory, within the plane-wave pseudopotential and projector-augmented-wave approaches. Quantum EXPRESSO owes its popularity to the ...

2003
Samir Sapra Michael Theobald Edmund M. Clarke

This paper introduces a new method for two-level logic minimization. Unlike previous approaches, the new method uses a SAT solver as an underlying engine. While the overall minimization strategy of the new method is based on the operators as defined in ESPRESSO-II, our SAT-based implementation is significantly different. The new minimizer SAT-ESPRESSO was found to perform 5–20 times faster than...

Journal: :Computer Physics Communications 2015
Changru Ma Layla Martin-Samos Stefano Fabris Alessandro Laio Simone Piccinin

We present QMMMW, a new program aimed at performing Quantum Mechanics/Molecular Mechanics (QM/MM) molecular dynamics. The package operates as a wrapper that patches PWscf code included in theQuantumESPRESSO distribution and LAMMPSMolecular Dynamics Simulator. It is designed with a paradigm based on three guidelines: (i) minimal amount of modifications on the parent codes, (ii) flexibility and c...

2013
Massimiliano Guarrasi Sandro Frigio Andrew Emerson Giovanni Erbacci

In this paper we will present part of the work carried out by CINECA in the framework of the PRACE-2IP project aimed to study the effect on performance due to the implementation of a 2D Domain Decomposition algorithm in DFT codes that use standard 1D (or slab) Parallel Domain Decomposition. The performance of this new algorithm are tested on two example applications: Quantum Espresso, a popular...

Journal: :Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2020

2016
Van-Thuy Phi Yuji Matsumoto

Part-whole relation, ormeronymy plays an important role in many domains. Among approaches to addressing the part-whole relation extraction task, the Espresso bootstrapping algorithm has proved to be effective by significantly improving recall while keeping high precision. In this paper, we first investigate the effect of using fine-grained subtypes and careful seed selection step on the perform...

Journal: :Computer Physics Communications 2006
Hans-Jörg Limbach Axel Arnold Bernward Mann Christian Holm

We describe a new program package that is designed to perform numerical Molecular Dynamics (MD) and Monte Carlo (MC) simulations for a broad class of soft matter systems in a parallel computing environment. Our main concept in developing ESPResSo was to provide a user friendly and fast simulation tool which serves at the same time as a research platform capable of rapidly incorporating the late...

Journal: :CoRR 2017
Fabrizio Pedersoli George Tzanetakis Andrea Tagliasacchi

There are many applications scenarios for which the computational performance and memory footprint of the prediction phase of Deep Neural Networks (DNNs) needs to be optimized. Binary Neural Networks (BDNNs) have been shown to be an effective way of achieving this objective. In this paper, we show how Convolutional Neural Networks (CNNs) can be implemented using binary representations. Espresso...

2018
Fabrizio Pedersoli George Tzanetakis

There are many applications scenarios for which the computational performance and memory footprint of the prediction phase of Deep Neural Networks (DNNs) need to be optimized. Binary Deep Neural Networks (BDNNs) have been shown to be an effective way of achieving this objective. In this paper, we show how Convolutional Neural Networks (CNNs) can be implemented using binary representations. Espr...

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