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ORCIDDiego Fabregat-Traver
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2010 – 2019
- 2019
[i18]Daniele G. Spampinato, Diego Fabregat-Traver, Markus Püschel, Paolo Bientinesi:
Program Generation for Linear Algebra Using Multiple Layers of DSLs. CoRR abs/1906.08613 (2019)- 2018
- [j8]Davor Davidovic
, Diego Fabregat-Traver, Markus Höhnerbach, Edoardo Di Napoli:
Accelerating the computation of FLAPW methods on heterogeneous architectures. Concurr. Comput. Pract. Exp. 30(24) (2018) - [j7]Diego Fabregat-Traver, Ahmed E. Ismail, Paolo Bientinesi:
Accelerating molecular dynamics codes by performance and accuracy modeling. J. Comput. Sci. 27: 77-90 (2018) - [c7]Daniele G. Spampinato, Diego Fabregat-Traver, Paolo Bientinesi, Markus Püschel:
Program generation for small-scale linear algebra applications. CGO 2018: 327-339 - [i17]Daniele G. Spampinato, Diego Fabregat-Traver, Paolo Bientinesi, Markus Püschel:
Program Generation for Small-Scale Linear Algebra Applications. CoRR abs/1805.04775 (2018) - 2017
- [i16]Davor Davidovic, Diego Fabregat-Traver, Markus Höhnerbach, Edoardo Di Napoli:
Accelerating the computation of FLAPW methods on heterogeneous architectures. CoRR abs/1712.07206 (2017) - 2016
- [j6]Alvaro Frank, Diego Fabregat-Traver, Paolo Bientinesi:
Large-scale linear regression: Development of high-performance routines. Appl. Math. Comput. 275: 411-421 (2016) - [c6]Diego Fabregat-Traver, Davor Davidovic, Markus Höhnerbach, Edoardo Di Napoli:
Hybrid CPU-GPU Generation of the Hamiltonian and Overlap Matrices in FLAPW Methods. JHPCS 2016: 200-211 - [i15]Diego Fabregat-Traver, Ahmed E. Ismail, Paolo Bientinesi:
Accelerating scientific codes by performance and accuracy modeling. CoRR abs/1608.04694 (2016) - [i14]Diego Fabregat-Traver, Davor Davidovic, Markus Höhnerbach, Edoardo Di Napoli:
Hybrid CPU-GPU generation of the Hamiltonian and Overlap matrices in FLAPW methods. CoRR abs/1611.00606 (2016) - 2015
- [j5]Elmar Peise, Diego Fabregat-Traver, Paolo Bientinesi:
High performance solutions for big-data GWAS. Parallel Comput. 42: 75-87 (2015) - [i13]Alvaro Frank, Diego Fabregat-Traver, Paolo Bientinesi:
Large-scale linear regression: Development of high-performance routines. CoRR abs/1504.07890 (2015) - 2014
- [j4]Diego Fabregat-Traver, Yurii S. Aulchenko, Paolo Bientinesi:
Solving sequences of generalized least-squares problems on multi-threaded architectures. Appl. Math. Comput. 234: 606-617 (2014) - [j3]Edoardo Di Napoli, Diego Fabregat-Traver, Gregorio Quintana-Ortí, Paolo Bientinesi:
Towards an efficient use of the BLAS library for multilinear tensor contractions. Appl. Math. Comput. 235: 454-468 (2014) - [j2]Diego Fabregat-Traver, Paolo Bientinesi:
Computing Petaflops over Terabytes of Data: The Case of Genome-Wide Association Studies. ACM Trans. Math. Softw. 40(4): 27:1-27:22 (2014) - [c5]Elmar Peise, Diego Fabregat-Traver, Paolo Bientinesi:
On the Performance Prediction of BLAS-based Tensor Contractions. PMBS@SC 2014: 193-212 - [i12]Elmar Peise, Diego Fabregat-Traver, Paolo Bientinesi:
High Performance Solutions for Big-data GWAS. CoRR abs/1403.6426 (2014) - [i11]Diego Fabregat-Traver:
Knowledge-Based Automatic Generation of Linear Algebra Algorithms and Code. CoRR abs/1404.3406 (2014) - [i10]Elmar Peise, Diego Fabregat-Traver, Paolo Bientinesi:
On the Performance Prediction of BLAS-based Tensor Contractions. CoRR abs/1409.8608 (2014) - [i9]Diego Fabregat-Traver, Paolo Bientinesi:
Automatic Generation of Loop-Invariants for Matrix Operations. CoRR abs/1410.0564 (2014) - [i8]Diego Fabregat-Traver, Paolo Bientinesi:
Knowledge-Based Automatic Generation of Partitioned Matrix Expressions. CoRR abs/1410.0567 (2014) - 2013
- [b1]Diego Fabregat-Traver:
Knowledge-based automatic generation of linear algebra algorithms and code. RWTH Aachen University, 2013, pp. 1-148 - [j1]Diego Fabregat-Traver, Paolo Bientinesi:
Application-tailored linear algebra algorithms: A search-based approach. Int. J. High Perform. Comput. Appl. 27(4): 426-439 (2013) - [c4]Elmar Peise, Diego Fabregat-Traver, Yurii S. Aulchenko, Paolo Bientinesi:
Algorithms for large-scale whole genome association analysis. EuroMPI 2013: 229-234 - [i7]Elmar Peise, Diego Fabregat-Traver, Yurii S. Aulchenko, Paolo Bientinesi:
Algorithms for Large-scale Whole Genome Association Analysis. CoRR abs/1304.2272 (2013) - [i6]Edoardo Di Napoli, Diego Fabregat-Traver, Gregorio Quintana-Ortí, Paolo Bientinesi:
Towards an Efficient Use of the BLAS Library for Multilinear Tensor Contractions. CoRR abs/1307.2100 (2013) - 2012
- [c3]Diego Fabregat-Traver, Paolo Bientinesi:
A Domain-Specific Compiler for Linear Algebra Operations. VECPAR 2012: 346-361 - [i5]Diego Fabregat-Traver, Paolo Bientinesi:
A Domain-Specific Compiler for Linear Algebra Operations. CoRR abs/1205.5975 (2012) - [i4]Diego Fabregat-Traver, Yurii S. Aulchenko, Paolo Bientinesi:
High-throughput Genome-wide Association Analysis for Single and Multiple Phenotypes. CoRR abs/1207.2169 (2012) - [i3]Diego Fabregat-Traver, Yurii S. Aulchenko, Paolo Bientinesi:
Solving Sequences of Generalized Least-Squares Problems on Multi-threaded Architectures. CoRR abs/1210.7325 (2012) - [i2]Diego Fabregat-Traver, Paolo Bientinesi:
Computing Petaflops over Terabytes of Data: The Case of Genome-Wide Association Studies. CoRR abs/1210.7683 (2012) - [i1]Diego Fabregat-Traver, Paolo Bientinesi:
Application-tailored Linear Algebra Algorithms: A search-based Approach. CoRR abs/1211.5904 (2012) - 2011
- [c2]Diego Fabregat-Traver, Paolo Bientinesi:
Knowledge-Based Automatic Generation of Partitioned Matrix Expressions. CASC 2011: 144-157 - [c1]Diego Fabregat-Traver, Paolo Bientinesi:
Automatic Generation of Loop-Invariants for Matrix Operations. ICCSA Workshops 2011: 82-92
Coauthor Index
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