42 citations · 45 across the 5 of their papers we have counts for
6 papers
An HPC Approach to Accelerate Tensor Decompositions
Markus Hellgren, Erna Begovic Kovac, Hans O. Karlsson +1
Quantum systems grow in complexity so rapidly that even modest models become difficult to simulate, creating a strong need for methods that can handle high-dimensional data, also k…
General framework for re-assuring numerical reliability in parallel Krylov solvers: A case of BiCGStab methods
Roman Iakymchuk, Jose I. Aliaga
Parallel implementations of Krylov subspace methods often help to accelerate the procedure of finding an approximate solution of a linear system. However, such parallelization coup…
Efficient and Eventually Consistent Collective Operations
Roman Iakymchuk, Amandio Faustino, Andrew Emerson +4
Collective operations are common features of parallel programming models that are frequently used in High-Performance (HPC) and machine/ deep learning (ML/ DL) applications. In str…
Reproducibility of Parallel Preconditioned Conjugate Gradient in Hybrid Programming Environments
Roman Iakymchuk, Maria Barreda, Stef Graillat +2
The Preconditioned Conjugate Gradient method is often employed for the solution of linear systems of equations arising in numerical simulations of physical phenomena. While being w…
White Paper from Workshop on Large-scale Parallel Numerical Computing Technology (LSPANC 2020): HPC and Computer Arithmetic toward Minimal-Precision Computing
Roman Iakymchuk, Daichi Mukunoki, Artur Podobas +15
In numerical computations, precision of floating-point computations is a key factor to determine the performance (speed and energy-efficiency) as well as the reliability (accuracy…
Reproducibility, accuracy and performance of the Feltor code and library on parallel computer architectures
Matthias Wiesenberger, Lukas Einkemmer, Markus Held +3
Feltor is a modular and free scientific software package. It allows developing platform independent code that runs on a variety of parallel computer architectures ranging from lapt…