24 papers · ranked by Valyu relevance
Fusong Ju, Xinran Wei, Lin Huang, Andrew J. Jenkins + 13 more
Disruption: DFT Software as a Service Authors: ['Fusong Ju' 'Xinran Wei' 'Lin Huang' 'Andrew J. Jenkins' 'Leo Xia' 'Jia Zhang' 'Jianwei Zhu' 'Han Yang' 'Bin Shao' 'Peggy Dai' 'David B. Williams-Young' 'Ashwin Mayya' 'Zahra Hooshmand' 'Alexandra Efimovskaya' 'Nathan A. Baker' 'Matthias Troyer' 'Hongbin Liu'] Density…
Wei Wang, Lifan Xu, John Cavazos, Howie H. Huang + 2 more
'Tobias Preis'] Recent developments in modern computational accelerators like Graphics Processing Units (GPUs) and coprocessors provide great opportunities for making scientific applications run faster than ever before. However, efficient parallelization of scientific code using new programming tools like CUDA requires…
Corey Nolet, Avantika Lal, Rajesh Ilango, Taurean Dyer + 3 more
Single-cell genomic technologies are rapidly improving our understanding of cellular heterogeneity in biological systems. In recent years, technological and computational improvements have continuously increased the scale of single-cell experiments, and now allow for millions of cells to be analyzed in a single…
Zachary Cooper-Baldock, Brenda Vara Almirall, Kiao Inthavong
Fluid Dynamics on HPC systems Authors: ['Zachary Cooper-Baldock' 'Brenda Vara Almirall' 'Kiao Inthavong'] Computational Fluid Dynamics (CFD) is the simulation of fluid flow undertaken with the use of computational hardware. The underlying equations are computationally challenging to solve and necessitate high…
Yongfei Wang, Junping Wang, Jiarui Tian, Lin Li + 4 more
'Fang Peng' 'Hu Ke' 'Alberto Marchisio'] Early warning of geological hazards requires monitoring extreme weather conditions, such as heavy rainfall. Atmospheric circulation models are used for weather forecasting and climate simulation. As a critical physical process in atmospheric circulation models, the…
Kyle E. Niemeyer, Chih‐Jen Sung
The progress made in accelerating simulations of fluid flow using GPUs, and the challenges that remain, are surveyed. The review first provides an introduction to GPU computing and programming, and discusses various considerations for improved performance. Case studies comparing the performance of CPU- and GPU-based…
Xin Wang, Bin Zhang, Xu Cao, Fei Liu + 2 more
Fluorescence molecular tomography (FMT) with early-photons can improve the spatial resolution and fidelity of the reconstructed results. However, its computing scale is always large which limits its applications. In this paper, we introduced an acceleration strategy for the early-photon FMT with graphics processing…
Eric Wright, Mauricio Ferrato, Alex Bryer, Robert Searles + 2 more
Experimental chemical shifts (CS) from solution and solid state magic-angle-spinning nuclear magnetic resonance spectra provide atomic level information for each amino acid within a protein or protein complex. However, structure determination of large complexes and assemblies based on NMR data alone remains challenging…
Erdal Mutlu, Ruiqin Tian, Bin Ren, Sriram Krishnamoorthy + 3 more
'Roberto Gioiosa' 'Jacques A. Pienaar' 'Gökçen Kestor'] The computational power increases over the past decades have greatly enhanced the ability to simulate chemical reactions and understand ever more complex transformations. Tensor contractions are the fundamental computational building block of these simulations.…
James T. Meech, Vasileios Tsoutsouras, Phillip Stanley‐Marbell
Most modern computing tasks have digital electronic input and output data. Due to these constraints imposed by real-world use cases of computer systems, any analog computing accelerator, whether analog electronic or optical, must perform an analog-to-digital conversion on its input data and a subsequent…
Authors not listed
As a prove of concept for experimental geochemistry, an advanced 3D numerical framework, here and after called Digital Twin (DT), of a diffusion experiment conducted at a synchrotron beamline, has been implemented using in-situ measurements data, physics-based modelling, a machine learning (ML) model, and parameter…
Chris Rackauckas, Yingbo Ma, Andreas Noack, Vaibhav Dixit + 10 more
Pharmacometric modeling establishes causal quantitative relationships between administered dose, tissue exposures, desired and undesired effects and patient’s risk factors. These models are employed to de-risk drug development and guide precision medicine decisions. However, pharmacometric tools have not been designed…
Hamed Khakzad, Yasaman Karami, Seyed Shahriar Arab
Protein tertiary structure prediction (PSP) is one of the most challenging problems in bioinformatics. Different methods have been introduced to solve this problem so far, but PSP is computationally intensive and belongs to the NP-hard class. One of the best solutions to accelerate PSP is the use of a massively…
Authors not listed
The complete active space self-consistent field (CASSCF) method is essential for describing complex photochemical processes, but its application in ab initio molecular dynamics is often limited by the computational cost associated with four-center two-electron repulsion integrals (ERIs). We present the first…
Authors not listed
Modeling multimetallic systems efficiently enables faster prediction of desirable chemical properties and design of new materials. This work describes an initial implementation for performing multireference wave function method localized active space self-consistent field (LASSCF) calculations through the use of…
Madushanka Manathunga, Hasan Metin Aktulga, Andreas W. Goetz, Kenneth M. Merz + 1 more
We have ported and optimized the GPU accelerated QUICK and AMBER based ab initio QM/MM implementation on AMD GPUs. This encompasses the entire Fock matrix build and force calculation in QUICK including one-electron integrals, two-electron repulsion integrals, exchange-correlation quadrature, and linear algebra…
Andrea Tangherloni, Marco S. Nobile, Paolo Cazzaniga, Giulia Capitoli + 4 more
Mathematical models of biochemical networks can largely facilitate the comprehension of the mechanisms at the basis of cellular processes, as well as the formulation of hypotheses that can then be tested with targeted laboratory experiments. However, two issues might hamper the achievement of fruitful outcomes. On the…
Authors not listed
The era of exascale computing presents both exciting opportunities and unique challenges for quantum mechanical simulations. While the transition from petaflops to exascale computing has been marked by a steady increase in computational power, the shift towards heterogeneous architectures, particularly the dominant…
Authors not listed
This comprehensive review examines the evolution of autonomous materials synthesis laboratories that integrate artificial intelligence with advanced robotics to accelerate discovery. Traditional materials development pipelines typically require 10-20 years, but self-driving laboratories (SDLs) and Materials…
David S. Cerutti, Rafal Wiewiora, Simon Boothroyd, Woody Sherman
The Structure and TOpology Replica Molecular Mechanics (STORMM) code is a next-generation molecular simulation engine and associated libraries optimized for performance on fast, multicore central processor units (CPUs) and graphics processing units (GPUs) with independent memory and tens of thousands of threads. STORMM…
Authors not listed
Computational chemistry has entered a new era where machine learning (ML) models—particularly graph neural networks and machine learning force fields—routinely deliver quantum mechanical accuracy at classical speeds, scaling to millions of atoms and reshaping workflows in drug discovery, catalysis, and materials…
Yann Garniron, Thomas Applencourt, Kevin Gasperich, Anouar Benali + 15 more
Quantum Package is an open-source programming environment for quantum chemistry specially designed for wave function methods. Its main goal is the development of determinant-driven selected configuration interaction (sCI) methods and multi-reference second-order perturbation theory (PT2). The determinant-driven…
Matthias Möller, C. Vuik
Quantum computing technologies have become a hot topic in academia and industry receiving much attention and financial support from all sides. Building a quantum computer that can be used practically is in itself an outstanding challenge that has become the 'new race to the moon'. Next to researchers and vendors of…
Felix Johannes Schmitt, Vahid Rostami, Martin Paul Nawrot
Spiking neural networks (SNN) represent the state-of-the-art approach to the biologically realistic modeling of nervous system function. The systematic calibration for multiple free model parameters is necessary to achieve robust network function and demands high computing power and large memory resources. Special…