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20202024
most citedThe Challenge of Stochastic Størmer-Verlet Thermostats Generating Correct Statistics

7 citations · 13 across the 4 of their papers we have counts for

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6 papers · 1 filter

physics.comp-ph2024

Efficient Mixed-Precision Matrix Factorization of the Inverse Overlap Matrix in Electronic Structure Calculations with AI-Hardware and GPUs

Adela Habib, Joshua Finkelstein, Anders M. N. Niklasson

In recent years, a new kind of accelerated hardware has gained popularity in the Artificial Intelligence (AI) and Machine Learning (ML) communities which enables extremely high-per…

physics.comp-ph2024

Hybrid programming-model strategies for GPU offloading of electronic structure calculation kernels

Jean-Luc Fattebert, Christian F. A. Negre, Joshua Finkelstein +6

To address the challenge of performance portability, and facilitate the implementation of electronic structure solvers, we developed the Basic Matrix Library (BML) and Parallel, Ra…

physics.comp-ph2022

Quantum perturbation theory using Tensor cores and a deep neural network

Joshua Finkelstein, Emanuel H. Rubensson, Susan M. Mniszewski +2

Time-independent quantum response calculations are performed using Tensor cores. This is achieved by mapping density matrix perturbation theory onto the computational structure of…

physics.comp-ph20216 cited

Bringing discrete-time Langevin splitting methods into agreement with thermodynamics

Joshua Finkelstein, Chungho Cheng, Giacomo Fiorin +2

In light of the recently published complete set of statistically correct Gronbech-Jensen (GJ) methods for discrete-time thermodynamics, we revise a differential operator splitting…

physics.comp-ph2021

Quantum-based Molecular Dynamics Simulations Using Tensor Cores

Joshua Finkelstein, Justin S. Smith, Susan M. Mniszewski +4

Tensor cores, along with tensor processing units, represent a new form of hardware acceleration specifically designed for deep neural network calculations in artificial intelligenc…

physics.comp-ph2021

Mixed Precision Fermi-Operator Expansion on Tensor Cores From a Machine Learning Perspective

Joshua Finkelstein, Justin Smith, Susan M. Mniszewski +4

We present a second-order recursive Fermi-operator expansion scheme using mixed precision floating point operations to perform electronic structure calculations using tensor core u…