We exploit the high memory bandwidth of AI-customized Cerebras CS-2 systems for seismic
processing. By leveraging low-rank matrix approximation, we fit memory-hungry seismic …

Adaptive Optics (AO) is a technology that permits to measure and mitigate the distortion
effects of atmospheric turbulence on optical beams. AO must operate in real-time by …

We are interested in solving linear systems arising from three applications:(1) kernel
methods in machine learning,(2) discretization of boundary integral equations from …

We present a general framework that couples the PaRSEC runtime system and the HiCMA
numerical library to solve challenging 3D data-sparse problems. Though formally dense …

With the aim of imaging subsurface discontinuities, seismic data recorded at the surface of
the Earth must be numerically re-positioned at locations in the subsurface where reflections …

Dynamic LR and QR factorization are fundamental problems that exist widely in the control
field. However, the existing solutions under noises are lack of convergence speed and anti …

We investigate a special class of data sparse rank-structured matrices that combine a flat
block low-rank (BLR) partitioning with the use of shared (called nested in the hierarchical …

We present a high-performance implementation of Seismic Redatuming by Inversion (SRI),
which combines algebraic compression with mixed-precision (MP) computations. Seismic …

We consider multilevel low rank (MLR) matrices, defined as a row and column permutation
of a sum of matrices, each one a block diagonal refinement of the previous one, with all …

The Radial Basis Function (RBF) technique is an interpolation method that produces high-
quality unstructured adaptive meshes. However, the RBF-based boundary problem …