21 citations · 191 across the 67 of their papers we have counts for
6 papers · 2 filters
Application-tailored Linear Algebra Algorithms: A search-based Approach
Diego Fabregat-Traver, Paolo Bientinesi
In this paper, we tackle the problem of automatically generating algorithms for linear algebra operations by taking advantage of problem-specific knowledge. In most situations, use…
Computing Petaflops over Terabytes of Data: The Case of Genome-Wide Association Studies
Diego Fabregat-Traver, Paolo Bientinesi
In many scientific and engineering applications, one has to solve not one but a sequence of instances of the same problem. Often times, the problems in the sequence are linked in a…
Solving Sequences of Generalized Least-Squares Problems on Multi-threaded Architectures
Diego Fabregat-Traver, Yurii Aulchenko, Paolo Bientinesi
Generalized linear mixed-effects models in the context of genome-wide association studies (GWAS) represent a formidable computational challenge: the solution of millions of correla…
Performance Modeling for Dense Linear Algebra
Elmar Peise, Paolo Bientinesi
It is well known that the behavior of dense linear algebra algorithms is greatly influenced by factors like target architecture, underlying libraries and even problem size; because…
A Domain-Specific Compiler for Linear Algebra Operations
Diego Fabregat-Traver, Paolo Bientinesi
We present a prototypical linear algebra compiler that automatically exploits domain-specific knowledge to generate high-performance algorithms. The input to the compiler is a targ…
High-Performance Solvers for Dense Hermitian Eigenproblems
Matthias Petschow, Elmar Peise, Paolo Bientinesi
We introduce a new collection of solvers - subsequently called EleMRRR - for large-scale dense Hermitian eigenproblems. EleMRRR solves various types of problems: generalized, stand…