21 citations · 191 across the 67 of their papers we have counts for
7 papers · 1 filter
Knowledge-Based Automatic Generation of Partitioned Matrix Expressions
Diego Fabregat-Traver, Paolo Bientinesi
In a series of papers it has been shown that for many linear algebra operations it is possible to generate families of algorithms by following a systematic procedure. Although powe…
Automatic Generation of Loop-Invariants for Matrix Operations
Diego Fabregat-Traver, Paolo Bientinesi
In recent years it has been shown that for many linear algebra operations it is possible to create families of algorithms following a very systematic procedure. We do not refer to…
On the Performance Prediction of BLAS-based Tensor Contractions
Elmar Peise, Diego Fabregat-Traver, Paolo Bientinesi
Tensor operations are surging as the computational building blocks for a variety of scientific simulations and the development of high-performance kernels for such operations is kn…
Cache-aware Performance Modeling and Prediction for Dense Linear Algebra
Elmar Peise, Paolo Bientinesi
Countless applications cast their computational core in terms of dense linear algebra operations. These operations can usually be implemented by combining the routines offered by s…
High Performance Solutions for Big-data GWAS
Elmar Peise, Diego Fabregat-Traver, Paolo Bientinesi
In order to associate complex traits with genetic polymorphisms, genome-wide association studies process huge datasets involving tens of thousands of individuals genotyped for mill…
A Study on the Influence of Caching: Sequences of Dense Linear Algebra Kernels
Elmar Peise, Paolo Bientinesi
It is universally known that caching is critical to attain high- performance implementations: In many situations, data locality (in space and time) plays a bigger role than optimiz…