4 citations · 8 across the 2 of their papers we have counts for
6 papers
Fireiron: A Scheduling Language for High-Performance Linear Algebra on GPUs
Bastian Hagedorn, Archibald Samuel Elliott, Henrik Barthels +2
Achieving high-performance GPU kernels requires optimizing algorithm implementations to the targeted GPU architecture. It is of utmost importance to fully use the compute and memor…
Linnea: Automatic Generation of Efficient Linear Algebra Programs
Henrik Barthels, Christos Psarras, Paolo Bientinesi
The translation of linear algebra computations into efficient sequences of library calls is a non-trivial task that requires expertise in both linear algebra and high-performance c…
Automatic Generation of Efficient Linear Algebra Programs
Henrik Barthels, Christos Psarras, Paolo Bientinesi
The level of abstraction at which application experts reason about linear algebra computations and the level of abstraction used by developers of high-performance numerical linear…
The Generalized Matrix Chain Algorithm
Henrik Barthels, Marcin Copik, Paolo Bientinesi
In this paper, we present a generalized version of the matrix chain algorithm to generate efficient code for linear algebra problems, a task for which human experts often invest da…
MatchPy: A Pattern Matching Library
Manuel Krebber, Henrik Barthels, Paolo Bientinesi
Pattern matching is a powerful tool for symbolic computations, based on the well-defined theory of term rewriting systems. Application domains include algebraic expressions, abstra…
Efficient Pattern Matching in Python
Manuel Krebber, Henrik Barthels, Paolo Bientinesi
Pattern matching is a powerful tool for symbolic computations. Applications include term rewriting systems, as well as the manipulation of symbolic expressions, abstract syntax tre…