2 citations · 2 across the 4 of their papers we have counts for
6 papers
Designing Machine Learning Surrogates using Outputs of Molecular Dynamics Simulations as Soft Labels
J. C. S. Kadupitiya, Nasim Anousheh, Vikram Jadhao
Molecular dynamics simulations are powerful tools to extract the microscopic mechanisms characterizing the properties of soft materials. We recently introduced machine learning sur…
Integrating Machine Learning with HPC-driven Simulations for Enhanced Student Learning
Vikram Jadhao, JCS Kadupitiya
We explore the idea of integrating machine learning (ML) with high performance computing (HPC)-driven simulations to address challenges in using simulations to teach computational…
Designing Surface Charge Patterns for Shape Control of Deformable Nanoparticles
Nicholas E. Brunk, JCS Kadupitiya, Vikram Jadhao
Designing reconfigurable materials based on deformable nanoparticles (NPs) hinges on an understanding of the energetically-favored shapes these NPs can adopt. Using simulations, we…
Modeling The Temporally Constrained Preemptions of Transient Cloud VMs
JCS Kadupitiya, Vikram Jadhao, Prateek Sharma
Transient cloud servers such as Amazon Spot instances, Google Preemptible VMs, and Azure Low-priority batch VMs, can reduce cloud computing costs by as much as , but can…
Machine Learning for Parameter Auto-tuning in Molecular Dynamics Simulations: Efficient Dynamics of Ions near Polarizable Nanoparticles
JCS Kadupitiya, Geoffrey C. Fox, Vikram Jadhao
Simulating the dynamics of ions near polarizable nanoparticles (NPs) using coarse-grained models is extremely challenging due to the need to solve the Poisson equation at every sim…
Learning Everywhere: Pervasive Machine Learning for Effective High-Performance Computation
Geoffrey Fox, James A. Glazier, JCS Kadupitiya +10
The convergence of HPC and data-intensive methodologies provide a promising approach to major performance improvements. This paper provides a general description of the interaction…