8 papers
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…
High-Performance Star-M SVD for Big Data Compression
Md Taufique Hussain, Grey Ballard, Aditya Devarakonda +3
In the era of big data, effectively compressing large datasets while performing complex mathematical operations is crucial. Tensor-based decomposition methods have shown superior c…
Rate-Distortion Bounds for Heterogeneous Random Fields on Finite Lattices
Sujata Sinha, Vishwas Rao, Robert Underwood +4
Since Shannon's foundational work, rate-distortion theory has defined the fundamental limits of lossy compression. Classical results, derived for memoryless and stationary ergodic…
Optimal sensor placement under model uncertainty in the weak-constraint 4D-Var framework
Alen Alexanderian, Hugo DÃaz, Vishwas Rao +1
In data assimilation, the model may be subject to uncertainties and errors. The weak-constraint data assimilation framework enables incorporating model uncertainty in the dynamics…
Parametric Hierarchical Matrix Approximations to Kernel Matrices
Abraham Khan, Chao Chen, Vishwas Rao +1
Kernel matrices are ubiquitous in computational mathematics, often arising from applications in machine learning and scientific computing. In two or three spatial or feature dimens…
Randomized Preconditioned Solvers for Strong Constraint 4D-Var Data Assimilation
Amit N. Subrahmanya, Vishwas Rao, Arvind K. Saibaba
The Strong Constraint 4D Variational (SC-4DVAR) data assimilation method is widely used in climate and weather applications. SC-4DVAR involves solving a minimization problem to com…