132 citations · 263 across the 9 of their papers we have counts for
10 papers
Perspectives on Sustainable Computational Science and Engineering
Julia Kowalski, Ann S. Almgren, Achim Basermann +43
Computational Science and Engineering (CSE) combines expertise at the intersection of engineering, applied mathematics, and computer science to form powerful methods for model-base…
Performance of linear solvers in tensor-train format on current multicore architectures
Melven Röhrig-Zöllner, Manuel Joey Becklas, Jonas Thies +1
Tensor networks are a class of algorithms aimed at reducing the computational complexity of high-dimensional problems. They are used in an increasing number of applications, from q…
(R)SE challenges in HPC
Jonas Thies, Melven Röhrig-Zöllner, Achim Basermann
We discuss some specific software engineering challenges in the field of high-performance computing, and argue that the slow adoption of SE tools and techniques is at least in part…
Performance of the low-rank tensor-train SVD (TT-SVD) for large dense tensors on modern multi-core CPUs
Melven Röhrig-Zöllner, Jonas Thies, Achim Basermann
There are several factorizations of multi-dimensional tensors into lower-dimensional components, known as `tensor networks'. We consider the popular `tensor-train' (TT) format and…
HeAT -- a Distributed and GPU-accelerated Tensor Framework for Data Analytics
Markus Götz, Daniel Coquelin, Charlotte Debus +9
To cope with the rapid growth in available data, the efficiency of data analysis and machine learning libraries has recently received increased attention. Although great advancemen…
Image Acquisition Planning for Earth Observation Satellites with a Quantum Annealer
Tobias Stollenwerk, Vincent Michaud, Elisabeth Lobe +3
We present a comparison study of state-of-the-art classical optimisation methods to a D-Wave 2000Q quantum annealer for the planning of Earth observation missions. The problem is t…
A Recursive Algebraic Coloring Technique for Hardware-Efficient Symmetric Sparse Matrix-Vector Multiplication
Christie L. Alappat, Georg Hager, Olaf Schenk +5
The symmetric sparse matrix-vector multiplication (SymmSpMV) is an important building block for many numerical linear algebra kernel operations or graph traversal applications. Par…
Benefits from using mixed precision computations in the ELPA-AEO and ESSEX-II eigensolver projects
Andreas Alvermann, Achim Basermann, Hans-Joachim Bungartz +30
We first briefly report on the status and recent achievements of the ELPA-AEO (Eigenvalue Solvers for Petaflop Applications - Algorithmic Extensions and Optimizations) and ESSEX II…
GHOST: Building blocks for high performance sparse linear algebra on heterogeneous systems
Moritz Kreutzer, Jonas Thies, Melven Röhrig-Zöllner +7
While many of the architectural details of future exascale-class high performance computer systems are still a matter of intense research, there appears to be a general consensus t…
Sparse matrix-vector multiplication on GPGPU clusters: A new storage format and a scalable implementation
Moritz Kreutzer, Georg Hager, Gerhard Wellein +3
Sparse matrix-vector multiplication (spMVM) is the dominant operation in many sparse solvers. We investigate performance properties of spMVM with matrices of various sparsity patte…