82 citations · 926 across the 70 of their papers we have counts for
8 papers · 1 filter
Interactive Debugger for Performance Portable Python HPC Kernels
Ivan Grigorik, Gabriel Kosmacher, George Biros +1
We propose PKDB, the first interactive debugger for GPU and multithreaded low-level kernels written in Python. Python is widely used in high performance computing (HPC), with frame…
VesNet: Neural network accelerated solver for simulating Stokesian vesicle suspensions
Shan Zhong, Gokberk Kabacaoglu, George Biros
Numerical simulation of deformable particle suspensions in Stokes flow is computationally expensive due to nonlinear fluid-structure interactions, evolving interfaces, and multisca…
A performance portable fast Ewald summation for Stokes flow
Gabriel Kosmacher, Ziyu Du, Joar Bagge +1
We present GPU algorithms for Ewald summation methods for accelerating N-body Stokes flow problems in periodic domains. Like most N-body codes, Ewald sums use a near-field/far-fiel…
IV-Net: A neural network for elliptic PDEs with random and highly varying coefficients
Shan Zhong, George Biros
We introduce a novel neural operator architecture designed to approximate solutions of linear elliptic partial differential equations with high-contrast, spatially varying coeffici…
LNODE: latent dynamics reveal the shared spatiotemporal structure of amyloid- progression
Zheyu Wen, George Biros
We present and analyze LNODE, a mechanism-based phenomenological model for amyloid beta (A) dynamics, calibrated using positron emission tomography (PET) imaging. A is a key…
Proximal-IMH: Proximal Posterior Proposals for Independent Metropolis-Hastings with Approximate Operators
Youguang Chen, George Biros
We consider the problem of sampling from a posterior distribution arising in Bayesian inverse problems in science, engineering, and imaging. Our method belongs to the family of ind…
Inverse problems for history-enriched linear model reduction
Arjun Vijaywargiya, George Biros
Standard projection-based model reduction for dynamical systems incurs closure error because it only accounts for instantaneous dependence on the resolved state. From the Mori-Zwan…
Latent-IMH: Efficient Bayesian Inference for Inverse Problems with Approximate Operators
Youguang Chen, George Biros
We study sampling from posterior distributions in Bayesian linear inverse problems where , the parameters to observables operator, is computationally expensive. In many applicat…