activity
20242026
collaborators

8 papers

cond-mat.mtrl-sci2026

Towards exascale fully relativistic pseudopotential density functional theory calculations enabled by mixed-precision computation and compressed-communication using residual based subspace iteration

Nikhil Kodali, Gourab Panigrahi, Nishant Gupta +6

Noncollinear (NC) magnetism and spin-orbit coupling (SOC) are indispensable for predictive ab initio materials simulations with pronounced relativistic effects and magnetic frustra…

cond-mat.mtrl-sci2026

Prototype-Guided Latent Alignment for Data-Efficient Fine-Tuning of Molecular Foundation Models

Rushikesh Pawar, Harshit Rawat, Ayush Kumar +1

Machine learning interatomic potentials (MLIPs) have transformed materials discovery by leveraging graph neural networks (GNNs) to predict material properties with near density fun…

physics.comp-ph2026

Accelerating finite-element-based projector augmented-wave density functional theory calculations with scalable GPU-centric computational methods

Kartick Ramakrishnan, Phani Motamarri

Accurate large-scale Kohn-Sham density functional theory (DFT) calculations are essential for modeling complex material systems, including interfaces, defects, nanoclusters, and tw…

physics.comp-ph2026

Residual-based Chebyshev filtered subspace iteration for sparse Hermitian eigenvalue problems tolerant to inexact matrix-vector products

Nikhil Kodali, Kartick Ramakrishnan, Phani Motamarri

Chebyshev Filtered Subspace Iteration (ChFSI) is widely used for computing a small subset of extremal eigenpairs from large matrices, particularly when the eigenpairs must be compu…

physics.comp-ph2025

Matrix-free algorithms for fast ab initio calculations on distributed CPU architectures using finite-element discretization

Gourab Panigrahi, Phani Motamarri

Finite-element (FE) discretisations have emerged as a powerful real-space alternative to large-scale Kohn-Sham density functional theory (DFT) calculations, offering systematic con…

cond-mat.mtrl-sci2025

Real-space methods for ab initio modelling of surfaces and interfaces under external potential bias

Kartick Ramakrishnan, Gopalakrishnan Sai Gautam, Phani Motamarri

Accurate ab initio modelling of surfaces and interfaces, especially under an applied external potential bias, is important for describing and characterizing various phenomena that…