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Dive into the research topics where David E. Bernholdt is active.

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Featured researches published by David E. Bernholdt.


Computer Physics Communications | 2000

High performance computational chemistry: An overview of NWChem a distributed parallel application☆

Ricky A. Kendall; Edoardo Aprà; David E. Bernholdt; Eric J. Bylaska; Michel Dupuis; George I. Fann; Robert J. Harrison; Jialin Ju; Jeffrey A. Nichols; Jarek Nieplocha; T.P. Straatsma; Theresa L. Windus; Adrian T. Wong

NWChem is the software package for computational chemistry on massively parallel computing systems developed by the High Performance Computational Chemistry Group for the Environmental Molecular Sciences Laboratory. The software provides a variety of modules for quantum mechanical and classical mechanical simulation. This article describes the design and some implementation details of the overall NWChem architecture. The architecture facilitates rapid development and portability of fully distributed application modules. We also delineate some of the functionality within NWChem and show performance of a few of the modules within NWChem.


ieee international conference on high performance computing data and analytics | 2006

A Component Architecture for High-Performance Scientific Computing

Benjamin A. Allan; Robert C. Armstrong; David E. Bernholdt; Felipe Bertrand; Kenneth Chiu; Tamara L. Dahlgren; Kostadin Damevski; Wael R. Elwasif; Thomas Epperly; Madhusudhan Govindaraju; Daniel S. Katz; James Arthur Kohl; Manoj Kumar Krishnan; Gary Kumfert; J. Walter Larson; Sophia Lefantzi; Michael J. Lewis; Allen D. Malony; Lois C. Mclnnes; Jarek Nieplocha; Boyana Norris; Steven G. Parker; Jaideep Ray; Sameer Shende; Theresa L. Windus; Shujia Zhou

The Common Component Architecture (CCA) provides a means for software developers to manage the complexity of large-scale scientific simulations and to move toward a plug-and-play environment for high-performance coputing. In the scientific computing context, component models also promote collaboration using independently developed software, thereby allowing particular individals or groups to focus on the aspects of greatest interest to them. The CCA supports parallel and distributed coputing as well as local high-performance connections between components in a language-independent manner. The design places minimal requirements on components and thus facilitates the integration of existing code into the CCA environment. The CCA model imposes minimal ovehead to minimize the impact on application performance. The focus on high performance distinguishes the CCA from most other component models. The CCA is being applied within an increasing range of disciplines, including cobustion research, global climate simulation, and computtional chemistry.


arXiv: Computational Engineering, Finance, and Science | 2005

The Earth System Grid: Supporting the Next Generation of Climate Modeling Research

David E. Bernholdt; Shishir Bharathi; David Brown; Kasidit Chanchio; Meili Chen; Ann L. Chervenak; Luca Cinquini; Bob Drach; Ian T. Foster; Peter Fox; José I. García; Carl Kesselman; Rob S. Markel; Don Middleton; Veronika Nefedova; Line C. Pouchard; Arie Shoshani; Alex Sim; Gary Strand; Dean N. Williams

Understanding the Earths climate system and how it might be changing is a preeminent scientific challenge. Global climate models are used to simulate past, present, and future climates, and experiments are executed continuously on an array of distributed supercomputers. The resulting data archive, spread over several sites, currently contains upwards of 100 TB of simulation data and is growing rapidly. Looking toward mid-decade and beyond, we must anticipate and prepare for distributed climate research data holdings of many petabytes. The Earth System Grid (ESG) is a collaborative interdisciplinary project aimed at addressing the challenge of enabling management, discovery, access, and analysis of these critically important datasets in a distributed and heterogeneous computational environment. The problem is fundamentally a Grid problem. Building upon the Globus toolkit and a variety of other technologies, ESG is developing an environment that addresses authentication, authorization for data access, large-scale data transport and management, services and abstractions for high-performance remote data access, mechanisms for scalable data replication, cataloging with rich semantic and syntactic information, data discovery, distributed monitoring, and Web-based portals for using the system.


Proceedings of the IEEE | 2005

Synthesis of High-Performance Parallel Programs for a Class of ab Initio Quantum Chemistry Models

Gerald Baumgartner; Alexander A. Auer; David E. Bernholdt; Alina Bibireata; Venkatesh Choppella; Daniel Cociorva; Xiaoyang Gao; Robert J. Harrison; So Hirata; Sriram Krishnamoorthy; Sandhya Krishnan; Chi-Chung Lam; Qingda Lu; Marcel Nooijen; Russell M. Pitzer; J. Ramanujam; P. Sadayappan; Alexander Sibiryakov

This paper provides an overview of a program synthesis system for a class of quantum chemistry computations. These computations are expressible as a set of tensor contractions and arise in electronic structure modeling. The input to the system is a a high-level specification of the computation, from which the system can synthesize high-performance parallel code tailored to the characteristics of the target architecture. Several components of the synthesis system are described, focusing on performance optimization issues that they address.


Concurrency and Computation: Practice and Experience | 2002

The CCA core specification in a distributed memory SPMD framework

Benjamin A. Allan; Robert C. Armstrong; Alicia P. Wolfe; Jaideep Ray; David E. Bernholdt; James Arthur Kohl

We present an overview of the Common Component Architecture (CCA) core specification and CCAFFEINE, a Sandia National Laboratories framework implementation compliant with the draft specification. CCAFFEINE stands for CCA Fast Framework Example In Need of Everything; that is, CCAFFEINE is fast, lightweight, and it aims to provide every framework service by using external, portable components instead of integrating all services into a single, heavy framework core. By fast, we mean that the CCAFFEINE glue does not get between components in a way that slows down their interactions. We present the CCAFFEINE solutions to several fundamental problems in the application of component software approaches to the construction of single program multiple data (SPMD) applications. We demonstrate the integration of components from three organizations, two within Sandia and one at Oak Ridge National Laboratory. We outline some requirements for key enabling facilities needed for a successful component approach to SPMD application building. Copyright


Molecular Physics | 2006

Automatic code generation for many-body electronic structure methods: the tensor contraction engine‡‡

Alexander A. Auer; Gerald Baumgartner; David E. Bernholdt; Alina Bibireata; Venkatesh Choppella; Daniel Cociorva; Xiaoyang Gao; Robert J. Harrison; Sriram Krishnamoorthy; Sandhya Krishnan; Chi-Chung Lam; Qingda Lu; Marcel Nooijen; Russell M. Pitzer; J. Ramanujam; P. Sadayappan; Alexander Sibiryakov

As both electronic structure methods and the computers on which they are run become increasingly complex, the task of producing robust, reliable, high-performance implementations of methods at a rapid pace becomes increasingly daunting. In this paper we present an overview of the Tensor Contraction Engine (TCE), a unique effort to address issues of both productivity and performance through automatic code generation. The TCE is designed to take equations for many-body methods in a convenient high-level form and acts like an optimizing compiler, producing an implementation tuned to the target computer system and even to the specific chemical problem of interest. We provide examples to illustrate the TCE approach, including the ability to target different parallel programming models, and the effects of particular optimizations.


Bulletin of the American Meteorological Society | 2009

The Earth System Grid: Enabling Access to Multimodel Climate Simulation Data

Dean N. Williams; Rachana Ananthakrishnan; David E. Bernholdt; S. Bharathi; D. Brown; M. Chen; A. L. Chervenak; L. Cinquini; R. Drach; I. T. Foster; P. Fox; Dan Fraser; J. A. Garcia; S. Hankin; P. Jones; D. E. Middleton; J. Schwidder; R. Schweitzer; Robert Schuler; A. Shoshani; F. Siebenlist; A. Sim; Warren G. Strand; Mei-Hui Su; N. Wilhelmi

By leveraging current technologies to manage distributed climate data in a unified virtual environment, the Earth System Grid (ESG) project is promoting data sharing between international research centers and diverse users. In transforming these data into a collaborative community resource, ESG is changing the way global climate research is conducted. Since ESGs production beginnings in 2004, its most notable accomplishment was to efficiently store and distribute climate simulation data of some 20 global coupled ocean-atmosphere models to the scores of scientific contributors to the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC); the IPCC collective scientific achievement was recognized by the award of a 2007 Nobel Peace Prize. Other international climate stakeholders such as the North American Regional Climate Change Assessment Program (NARCCAP) and the developers of the Community Climate System Model (CCSM) and of the Climate Science Computational End Station (CC...


conference on high performance computing (supercomputing) | 2002

A High-Level Approach to Synthesis of High-Performance Codes for Quantum Chemistry

Gerald Baumgartner; David E. Bernholdt; Daniel Cociorva; Robert J. Harrison; So Hirata; Chi-Chung Lam; Marcel Nooijen; Russell M. Pitzer; J. Ramanujam; P. Sadayappan

This paper discusses an approach to the synthesis of high-performance parallel programs for a class of computations encountered in quantum chemistry and physics. These computations are expressible as a set of tensor contractions and arise in electronic structure modeling. An overview is provided of the synthesis system, that transforms a high-level specification of the computation into high-performance parallel code, tailored to the characteristics of the target architecture. An example from computational chemistry is used to illustrate how different code structures are generated under different assumptions of available memory on the target computer.


Journal of Chemical Physics | 1998

Fitting basis sets for the RI-MP2 approximate second-order many-body perturbation theory method

David E. Bernholdt; Robert J. Harrison

The “resolution of the identity” integral approximation applied to second-order many-body perturbation theory, or RI-MP2, method offers improved computational performance compared to traditional (exact) second-order perturbation theory calculations, but introduces a new auxiliary or “fitting basis set” into the method. We develop fitting basis sets for use with the correlation consistent cc-pVDZ and cc-pVTZ atomic orbital basis sets for the atoms H-Ne. These fitting sets are designed to reproduce exact second-order results for a set of 32 test cases, including a variety of reaction energies, weak interactions, and electrostatic properties, to better than 1% error averaged across all tests and less than 2% error in any individual case. Although the RI-MP2 method is primarily targeted to large-scale calculations, it offers substantial performance improvements even for the small molecules used in these test cases.


programming language design and implementation | 2002

Space-time trade-off optimization for a class of electronic structure calculations

Daniel Cociorva; Gerald Baumgartner; Chi-Chung Lam; P. Sadayappan; J. Ramanujam; Marcel Nooijen; David E. Bernholdt; Robert J. Harrison

The accurate modeling of the electronic structure of atoms and molecules is very computationally intensive. Many models of electronic structure, such as the Coupled Cluster approach, involve collections of tensor contractions. There are usually a large number of alternative ways of implementing the tensor contractions, representing different trade-offs between the space required for temporary intermediates and the total number of arithmetic operations. In this paper, we present an algorithm that starts with an operation-minimal form of the computation and systematically explores the possible space-time trade-offs to identify the form with lowest cost that fits within a specified memory limit. Its utility is demonstrated by applying it to a computation representative of a component in the CCSD(T) formulation in the NWChem quantum chemistry suite from Pacific Northwest National Laboratory.

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Wael R. Elwasif

Oak Ridge National Laboratory

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James Arthur Kohl

Oak Ridge National Laboratory

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Aniruddha G. Shet

Oak Ridge National Laboratory

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J. Ramanujam

Louisiana State University

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