4 citations · 14 across the 16 of their papers we have counts for
5 papers · 1 filter
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…
High-throughput Genome-wide Association Analysis for Single and Multiple Phenotypes
Diego Fabregat-Traver, Yurii S. Aulchenko, Paolo Bientinesi
The variance component tests used in genomewide association studies of thousands of individuals become computationally exhaustive when multiple traits are analysed in the context o…
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…