The Super Instruction Architecture

Deumens, Erik; Lotrich, Victor F.; Perera, Ajith; Bartlett, Rodney J.; Jindal, Nakul; Sanders, Beverly A.

doi:10.1016/b978-0-444-53835-2.00008-0

Cited by 11 publications

(10 citation statements)

References 21 publications

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“…[185][186][187][188] The TCE development has since been followed by several other efforts toward enabling scalable tensor libraries. This includes Super Instruction Assembly Language (SIAL), 144,189 Cyclop Tensor Framework (CTF), 190 TiledArray framework, 191 and Libtensor, 192 which have been used to develop scalable implementations of CC methods.…”

Section: Articlementioning

confidence: 99%

NWChem: Past, present, and future

Aprà

Bylaska

Jong

et al. 2020

The Journal of Chemical Physics

528

289

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Specialized computational chemistry packages have permanently reshaped the landscape of chemical and materials science by providing tools to support and guide experimental efforts and for the prediction of atomistic and electronic properties. In this regard, electronic structure packages have played a special role by using first-principle-driven methodologies to model complex chemical and materials processes. Over the past few decades, the rapid development of computing technologies and the tremendous increase in computational power have offered a unique chance to study complex transformations using sophisticated and predictive many-body techniques that describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, novel parallel algorithms have been able to take advantage of computational resources to address the polynomial scaling of electronic structure methods. In this paper, we briefly review the NWChem computational chemistry suite, including its history, design principles, parallel tools, current capabilities, outreach, and outlook.

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Section: Articlementioning

confidence: 99%

NWChem: Past, present, and future

Aprà

Bylaska

Jong

et al. 2020

The Journal of Chemical Physics

528

289

View full text Add to dashboard Cite

show abstract

“…The emergence of parallel computing has also triggered a significant effort toward automatic generation of scalable CC codes, which resulted in the development of specialized systems that integrate elements of symbolic algebra for manipulating and optimizing tensor expressions with efficient parallel tensor libraries. Specialized distributed-memory (or in some cases sharedmemory) libraries for automatic tensor blocking, tensor redistribution, and efficient utilization of tensor symmetries such as Tensor Contraction Engine (TCE) 194,195 , super instruction assembly language (SIAL) 110,196 , libtensor 197 , Cyclops Tensor Framework (CTF) [198][199][200] , and TiledArray (TA) 201 play a key role in enabling high-accuracy CC methods in many community codes including NWChem 202 , Aquarius 203 , CFOUR 204 , MPQC 38 , Q-Chem 39 , ACES 24 , and MRCC 205 . Below, three of these tensor packages, TCE, TAMM, and TA are discussed as relevant to the NWChem (TCE) and NWChemEx (TAMM and TA) packages.…”

Section: Tensor Methodsmentioning

confidence: 99%

From NWChem to NWChemEx: Evolving with the Computational Chemistry Landscape

et al. 2021

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Since the advent of the first computers, chemists have been at the forefront of using computers to understand and solve complex chemical problems. As the hardware and software have evolved, so have the theoretical and computational chemistry methods and algorithms. Parallel computers clearly changed the common computing paradigm in the late 1970s and 80s, and the field has again seen a paradigm shift with the advent of graphical processing units. This review explores the challenges and some of the solutions in transforming software from the terascale to the petascale and now to the upcoming exascale computers. While discussing the field in general, NWChem and its redesign, NWChemEx, will be highlighted as one of the early co-design projects to take advantage of massively parallel computers and emerging software standards to enable large scientific challenges to be tackled.

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“…Previously, to ease these demands for large many-body calculations and new many-body theory developments, several specialized parallel tensor algebra systems have been developed. [55][56][57][58][59][60][61][62] Progress has been made for automated code generators, memory reduction, and the real-space many-body calculations. To further manipulate the tensor contractions on the complex space as required by the new GFCC approach, a more efficient tensor algebra library designed for generalized many-body calculations is needed.…”

Section: Tensor Algebra For Many-body Methodsmentioning

confidence: 99%

GFCCLib: Scalable and Efficient Coupled-Cluster Green's Function Library for Accurately Tackling Many Body Electronic Structure Problems

Peng,

Panyala,

Kowalski

et al. 2020

Preprint

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Coupled-cluster Green's function (GFCC) calculation has drawn much attention in the recent years for targeting the molecular and material electronic structure problems from a many-body perspective in a systematically improvable way. However, GFCC calculations on scientific computing clusters usually suffer from expensive higher dimensional tensor contractions in the complex space, expensive inter-process communication, and severe load imbalance, which limits it's routine use for tackling electronic structure problems. Here we present a numerical library prototype that is specifically designed for large-scale GFCC calculations. The design of the library is focused on a systematically optimal computing strategy to improve its scalability and efficiency.The performance of the library is demonstrated by the relevant profiling analysis of running GFCC calculations on remote giant computing clusters. The capability of the library is highlighted by computing a wide near valence band of a fullerene C60 molecule for the first time at the GFCCSD level that shows excellent agreement with the experimental spectrum.

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The Super Instruction Architecture

Cited by 11 publications

References 21 publications

NWChem: Past, present, and future

NWChem: Past, present, and future

From NWChem to NWChemEx: Evolving with the Computational Chemistry Landscape

GFCCLib: Scalable and Efficient Coupled-Cluster Green's Function Library for Accurately Tackling Many Body Electronic Structure Problems

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