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ORCIDPaolo Bientinesi
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- affiliation: Umea University, Sweden
- affiliation (former): RWTH Aachen University, Germany
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2020 – today
- 2023
[i67]Francisco López, Lars Karlsson, Paolo Bientinesi:
The Essential Algorithms for the Matrix Chain. CoRR abs/2303.17352 (2023)- 2022
- [j38]Edoardo Di Napoli, Paolo Bientinesi, Jiajia Li, André Uschmajew:
Editorial: High-performance tensor computations in scientific computing and data science. Frontiers Appl. Math. Stat. 8 (2022) - [j37]Christos Psarras
, Lars Karlsson, Rasmus Bro, Paolo Bientinesi:
Accelerating Jackknife Resampling for the Canonical Polyadic Decomposition. Frontiers Appl. Math. Stat. 8: 830270 (2022) - [j36]Christos Psarras, Henrik Barthels, Paolo Bientinesi:
The Linear Algebra Mapping Problem. Current State of Linear Algebra Languages and Libraries. ACM Trans. Math. Softw. 48(3): 26:1-26:30 (2022) - [j35]Christos Psarras, Lars Karlsson, Rasmus Bro, Paolo Bientinesi:
Algorithm 1026: Concurrent Alternating Least Squares for Multiple Simultaneous Canonical Polyadic Decompositions. ACM Trans. Math. Softw. 48(3): 34:1-34:20 (2022) - [j34]Marcin Copik, Tobias Grosser, Torsten Hoefler, Paolo Bientinesi, Benjamin Berkels:
Work-Stealing Prefix Scan: Addressing Load Imbalance in Large-Scale Image Registration. IEEE Trans. Parallel Distributed Syst. 33(3): 523-535 (2022) - [c36]Francisco López, Lars Karlsson, Paolo Bientinesi:
FLOPs as a Discriminant for Dense Linear Algebra Algorithms. ICPP 2022: 11:1-11:10 - [c35]Aravind Sankaran, Navid Akbari Alashti, Christos Psarras, Paolo Bientinesi:
Benchmarking the Linear Algebra Awareness of TensorFlow and PyTorch. IPDPS Workshops 2022: 924-933 - [c34]Aravind Sankaran, Paolo Bientinesi:
A Test for FLOPs as a Discriminant for Linear Algebra Algorithms. SBAC-PAD 2022: 221-230 - [i66]Aravind Sankaran, Navid Akbari Alashti, Christos Psarras, Paolo Bientinesi:
Benchmarking the Linear Algebra Awareness of TensorFlow and PyTorch. CoRR abs/2202.09888 (2022) - [i65]Francisco López, Lars Karlsson, Paolo Bientinesi:
FLOPs as a Discriminant for Dense Linear Algebra Algorithms. CoRR abs/2207.02070 (2022) - [i64]Lorenzo Chelini, Henrik Barthels, Paolo Bientinesi, Marcin Copik, Tobias Grosser, Daniele G. Spampinato:
MOM: Matrix Operations in MLIR. CoRR abs/2208.10391 (2022) - [i63]Aravind Sankaran, Paolo Bientinesi:
A Test for FLOPs as a Discriminant for Linear Algebra Algorithms. CoRR abs/2209.03258 (2022) - [i62]Paolo Bientinesi, David A. Ham, Furong Huang, Paul H. J. Kelly, P. Sadayappan, Edward Stow:
Tensor Computations: Applications and Optimization (Dagstuhl Seminar 22101). Dagstuhl Reports 12(3): 1-14 (2022) - 2021
- [j33]Konrad Kollnig, Paolo Bientinesi, Edoardo Di Napoli:
Rational Spectral Filters with Optimal Convergence Rate. SIAM J. Sci. Comput. 43(4): A2660-A2684 (2021) - [j32]Henrik Barthels, Christos Psarras, Paolo Bientinesi:
Linnea: Automatic Generation of Efficient Linear Algebra Programs. ACM Trans. Math. Softw. 47(3): 22:1-22:26 (2021) - [c33]Aravind Sankaran, Paolo Bientinesi:
Performance Comparison for Scientific Computations on the Edge via Relative Performance. IPDPS Workshops 2021: 887-895 - [c32]Mickaël Zehren, Marco Alunno, Paolo Bientinesi:
ADTOF: A large dataset of non-synthetic music for automatic drum transcription. ISMIR 2021: 818-824 - [i61]Aravind Sankaran, Paolo Bientinesi:
Performance Comparison for Scientific Computations on the Edge via Relative Performance. CoRR abs/2102.12740 (2021) - [i60]Christos Psarras, Lars Karlsson, Paolo Bientinesi:
The landscape of software for tensor computations. CoRR abs/2103.13756 (2021) - [i59]Mickaël Zehren, Marco Alunno, Paolo Bientinesi:
ADTOF: A large dataset of non-synthetic music for automatic drum transcription. CoRR abs/2111.11737 (2021) - [i58]Christos Psarras, Lars Karlsson, Rasmus Bro, Paolo Bientinesi:
Accelerating jackknife resampling for the Canonical Polyadic Decomposition. CoRR abs/2112.03985 (2021) - 2020
- [j31]Jure Vreca, Karl J. X. Sturm, Ernest Gungl, Farhad Merchant, Paolo Bientinesi, Rainer Leupers, Zmago Brezocnik:
Accelerating Deep Learning Inference in Constrained Embedded Devices Using Hardware Loops and a Dot Product Unit. IEEE Access 8: 165913-165926 (2020) - [c31]Henrik Barthels, Christos Psarras, Paolo Bientinesi:
Automatic Generation of Efficient Linear Algebra Programs. PASC 2020: 1:1-1:11 - [i57]Konrad Kollnig, Paolo Bientinesi, Edoardo Di Napoli:
Rational spectral filters with optimal convergence rate. CoRR abs/2001.04184 (2020) - [i56]Mickaël Zehren, Marco Alunno, Paolo Bientinesi:
Automatic Detection of Cue Points for DJ Mixing. CoRR abs/2007.08411 (2020) - [i55]Christos Psarras, Lars Karlsson, Paolo Bientinesi:
Concurrent Alternating Least Squares for multiple simultaneous Canonical Polyadic Decompositions. CoRR abs/2010.04678 (2020) - [i54]Aravind Sankaran, Paolo Bientinesi:
Robust Ranking of Linear Algebra Algorithms via Relative Performance. CoRR abs/2010.07226 (2020) - [i53]Marcin Copik, Tobias Grosser, Torsten Hoefler, Paolo Bientinesi, Benjamin Berkels:
Work-stealing prefix scan: Addressing load imbalance in large-scale image registration. CoRR abs/2010.12478 (2020) - [i52]Paolo Bientinesi, David A. Ham, Furong Huang, Paul H. J. Kelly, Christian Lengauer, Saday Sadayappan:
Tensor Computations: Applications and Optimization (Dagstuhl Seminar 20111). Dagstuhl Reports 10(3): 58-70 (2020)
2010 – 2019
- 2019
- [j30]Elmar Peise, Paolo Bientinesi:
The ELAPS framework: Experimental Linear Algebra Performance Studies. Int. J. High Perform. Comput. Appl. 33(2) (2019) - [j29]Markus Höhnerbach, Paolo Bientinesi:
Accelerating AIREBO: Navigating the Journey from Legacy to High-Performance Code. J. Comput. Chem. 40(14): 1471-1482 (2019) - [j28]Paul Springer, Devin Matthews, Paolo Bientinesi:
Spin Summations: A High-Performance Perspective. ACM Trans. Math. Softw. 45(1): 10:1-10:22 (2019) - [i51]William McDoniel, Paolo Bientinesi:
A Timer-Augmented Cost Function for Load Balanced DSMC. CoRR abs/1902.06040 (2019) - [i50]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) - [i49]Henrik Barthels, Christos Psarras, Paolo Bientinesi:
Automatic Generation of Efficient Linear Algebra Programs. CoRR abs/1907.02778 (2019) - [i48]Christos Psarras, Henrik Barthels, Paolo Bientinesi:
The Linear Algebra Mapping Problem. CoRR abs/1911.09421 (2019) - [i47]Henrik Barthels, Christos Psarras, Paolo Bientinesi:
Linnea: Automatic Generation of Efficient Linear Algebra Programs. CoRR abs/1912.12924 (2019) - 2018
- [j27]Diego Fabregat-Traver, Ahmed E. Ismail, Paolo Bientinesi:
Accelerating molecular dynamics codes by performance and accuracy modeling. J. Comput. Sci. 27: 77-90 (2018) - [j26]Paul Springer, Paolo Bientinesi:
Design of a High-Performance GEMM-like Tensor-Tensor Multiplication. ACM Trans. Math. Softw. 44(3): 28:1-28:29 (2018) - [c30]Henrik Barthels, Marcin Copik, Paolo Bientinesi:
The generalized matrix chain algorithm. CGO 2018: 138-148 - [c29]Daniele G. Spampinato, Diego Fabregat-Traver, Paolo Bientinesi, Markus Püschel:
Program generation for small-scale linear algebra applications. CGO 2018: 327-339 - [c28]Tina Raissi, Alessandro Tibo, Paolo Bientinesi:
Extended Pipeline for Content-Based Feature Engineering in Music Genre Recognition. ICASSP 2018: 2661-2665 - [c27]William McDoniel, Paolo Bientinesi:
A Timer-Augmented Cost Function for Load Balanced DSMC. VECPAR 2018: 160-173 - [i46]Henrik Barthels, Marcin Copik, Paolo Bientinesi:
The Generalized Matrix Chain Algorithm. CoRR abs/1804.04021 (2018) - [i45]Daniele G. Spampinato, Diego Fabregat-Traver, Paolo Bientinesi, Markus Püschel:
Program Generation for Small-Scale Linear Algebra Applications. CoRR abs/1805.04775 (2018) - [i44]Tina Raissi, Alessandro Tibo, Paolo Bientinesi:
Extended pipeline for content-based feature engineering in music genre recognition. CoRR abs/1805.05324 (2018) - [i43]Markus Höhnerbach, Paolo Bientinesi:
Optimizing AIREBO: Navigating the Journey from Complex Legacy Code to High Performance. CoRR abs/1810.07026 (2018) - 2017
- [j25]Edoardo Di Napoli, Elmar Peise, Markus Hrywniak, Paolo Bientinesi:
High-performance generation of the Hamiltonian and Overlap matrices in FLAPW methods. Comput. Phys. Commun. 211: 61-72 (2017) - [j24]Paul Springer, Jeff R. Hammond, Paolo Bientinesi:
TTC: A High-Performance Compiler for Tensor Transpositions. ACM Trans. Math. Softw. 44(2): 15:1-15:21 (2017) - [j23]Elmar Peise, Paolo Bientinesi:
Algorithm 979: Recursive Algorithms for Dense Linear Algebra - The ReLAPACK Collection. ACM Trans. Math. Softw. 44(2): 16:1-16:19 (2017) - [c26]Henrik Barthels, Paolo Bientinesi:
Linnea: Compiling Linear Algebra Expressions to High-Performance Code. PASCO@ISSAC 2017: 1:1-1:3 - [c25]Paul Springer, Tong Su, Paolo Bientinesi:
HPTT: a high-performance tensor transposition C++ library. ARRAY@PLDI 2017: 56-62 - [c24]Manuel Krebber, Henrik Barthels, Paolo Bientinesi:
Efficient Pattern Matching in Python. PyHPC@SC 2017: 2:1-2:9 - [c23]Manuel Krebber, Henrik Bartels, Paolo Bientinesi:
MatchPy: A Pattern Matching Library. SciPy 2017: 73-80 - [c22]William McDoniel, Markus Höhnerbach, Rodrigo Canales, Ahmed E. Ismail, Paolo Bientinesi:
LAMMPS' PPPM Long-Range Solver for the Second Generation Xeon Phi. ISC 2017: 61-78 - [i42]Paul Springer, Ahmed E. Ismail, Paolo Bientinesi:
A Scalable, Linear-Time Dynamic Cutoff Algorithm for Molecular Dynamics. CoRR abs/1701.05242 (2017) - [i41]William McDoniel, Markus Höhnerbach, Rodrigo Canales, Ahmed E. Ismail, Paolo Bientinesi:
LAMMPS' PPPM Long-Range Solver for the Second Generation Xeon Phi. CoRR abs/1702.04250 (2017) - [i40]Paul Springer, Tong Su, Paolo Bientinesi:
HPTT: A High-Performance Tensor Transposition C++ Library. CoRR abs/1704.04374 (2017) - [i39]Paul Springer, Devin Matthews, Paolo Bientinesi:
Spin Summations: A High-Performance Perspective. CoRR abs/1705.06661 (2017) - [i38]Manuel Krebber, Henrik Barthels, Paolo Bientinesi:
Efficient Pattern Matching in Python. CoRR abs/1710.00077 (2017) - [i37]Markus Höhnerbach, Ahmed E. Ismail, Paolo Bientinesi:
The Tersoff many-body potential: Sustainable performance through vectorization. CoRR abs/1710.00882 (2017) - [i36]Manuel Krebber, Henrik Barthels, Paolo Bientinesi:
MatchPy: A Pattern Matching Library. CoRR abs/1710.06915 (2017) - [i35]Ali Tarzan, Marco Alunno, Paolo Bientinesi:
Assessment of sound spatialisation algorithms for sonic rendering with headsets. CoRR abs/1711.09234 (2017) - 2016
- [j22]Alvaro Frank, Diego Fabregat-Traver, Paolo Bientinesi:
Large-scale linear regression: Development of high-performance routines. Appl. Math. Comput. 275: 411-421 (2016) - [c21]Paul Springer, Aravind Sankaran, Paolo Bientinesi:
TTC: a tensor transposition compiler for multiple architectures. ARRAY@PLDI 2016: 41-46 - [c20]Markus Höhnerbach, Ahmed E. Ismail, Paolo Bientinesi:
The vectorization of the tersoff multi-body potential: an exercise in performance portability. SC 2016: 69-81 - [i34]Daniel Tameling, Paolo Bientinesi, Ahmed E. Ismail:
A Note on Time Measurements in LAMMPS. CoRR abs/1602.05566 (2016) - [i33]Edoardo Di Napoli, Elmar Peise, Markus Hrywniak, Paolo Bientinesi:
High-performance generation of the Hamiltonian and Overlap matrices in FLAPW methods. CoRR abs/1602.06589 (2016) - [i32]Elmar Peise, Paolo Bientinesi:
Recursive Algorithms for Dense Linear Algebra: The ReLAPACK Collection. CoRR abs/1602.06763 (2016) - [i31]Paul Springer, Jeff R. Hammond, Paolo Bientinesi:
TTC: A high-performance Compiler for Tensor Transpositions. CoRR abs/1603.02297 (2016) - [i30]Paul Springer, Paolo Bientinesi:
Design of a high-performance GEMM-like Tensor-Tensor Multiplication. CoRR abs/1607.00145 (2016) - [i29]Paul Springer, Aravind Sankaran, Paolo Bientinesi:
TTC: A Tensor Transposition Compiler for Multiple Architectures. CoRR abs/1607.01249 (2016) - [i28]Markus Höhnerbach, Ahmed E. Ismail, Paolo Bientinesi:
The Vectorization of the Tersoff Multi-Body Potential: An Exercise in Performance Portability. CoRR abs/1607.02904 (2016) - [i27]Diego Fabregat-Traver, Ahmed E. Ismail, Paolo Bientinesi:
Accelerating scientific codes by performance and accuracy modeling. CoRR abs/1608.04694 (2016) - [i26]Rodrigo Canales, Elmar Peise, Paolo Bientinesi:
Large Scale Parallel Computations in R through Elemental. CoRR abs/1610.07310 (2016) - [i25]Henrik Barthels, Paolo Bientinesi:
The Matrix Chain Algorithm to Compile Linear Algebra Expressions. CoRR abs/1611.05660 (2016) - 2015
- [j21]Paolo Bientinesi, José R. Herrero, Enrique S. Quintana-Ortí, Robert Strzodka:
Parallel computing on graphics processing units and heterogeneous platforms. Concurr. Comput. Pract. Exp. 27(6): 1525-1527 (2015) - [j20]Elmar Peise, Diego Fabregat-Traver, Paolo Bientinesi:
High performance solutions for big-data GWAS. Parallel Comput. 42: 75-87 (2015) - [c19]Zoltán Endre Rákossy, Dominik Stengele, Axel Acosta-Aponte, Saumitra Chafekar, Paolo Bientinesi, Anupam Chattopadhyay:
Scalable and Efficient Linear Algebra Kernel Mapping for Low Energy Consumption on the Layers CGRA. ARC 2015: 301-310 - [c18]Paul Springer, Ahmed E. Ismail, Paolo Bientinesi:
A Scalable, Linear-Time Dynamic Cutoff Algorithm for Molecular Dynamics. ISC 2015: 155-170 - [i24]Alvaro Frank, Diego Fabregat-Traver, Paolo Bientinesi:
Large-scale linear regression: Development of high-performance routines. CoRR abs/1504.07890 (2015) - [i23]Elmar Peise, Paolo Bientinesi:
The ELAPS Framework: Experimental Linear Algebra Performance Studies. CoRR abs/1504.08035 (2015) - 2014
- [j19]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) - [j18]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) - [j17]Matthias Petschow, Enrique S. Quintana-Ortí, Paolo Bientinesi:
Improved Accuracy and Parallelism for MRRR-Based Eigensolvers - A Mixed Precision Approach. SIAM J. Sci. Comput. 36(2) (2014) - [j16]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) - [c17]Elmar Peise, Diego Fabregat-Traver, Paolo Bientinesi:
On the Performance Prediction of BLAS-based Tensor Contractions. PMBS@SC 2014: 193-212 - [c16]Elmar Peise, Paolo Bientinesi:
A Study on the Influence of Caching: Sequences of Dense Linear Algebra Kernels. VECPAR 2014: 245-258 - [e1]Dieter an Mey, Michael Alexander, Paolo Bientinesi, Mario Cannataro, Carsten Clauss, Alexandru Costan, Gabor Kecskemeti, Christine Morin, Laura Ricci, Julio Sahuquillo, Martin Schulz, Vittorio Scarano, Stephen L. Scott, Josef Weidendorfer:
Euro-Par 2013: Parallel Processing Workshops - BigDataCloud, DIHC, FedICI, HeteroPar, HiBB, LSDVE, MHPC, OMHI, PADABS, PROPER, Resilience, ROME, and UCHPC 2013, Aachen, Germany, August 26-27, 2013. Revised Selected Papers. Lecture Notes in Computer Science 8374, Springer 2014, ISBN 978-3-642-54419-4 [contents] - [i22]Elmar Peise, Paolo Bientinesi:
A Study on the Influence of Caching: Sequences of Dense Linear Algebra Kernels. CoRR abs/1402.5897 (2014) - [i21]Elmar Peise, Diego Fabregat-Traver, Paolo Bientinesi:
High Performance Solutions for Big-data GWAS. CoRR abs/1403.6426 (2014) - [i20]Elmar Peise, Paolo Bientinesi:
Cache-aware Performance Modeling and Prediction for Dense Linear Algebra. CoRR abs/1409.8602 (2014) - [i19]Elmar Peise, Diego Fabregat-Traver, Paolo Bientinesi:
On the Performance Prediction of BLAS-based Tensor Contractions. CoRR abs/1409.8608 (2014) - [i18]Diego Fabregat-Traver, Paolo Bientinesi:
Automatic Generation of Loop-Invariants for Matrix Operations. CoRR abs/1410.0564 (2014) - [i17]Diego Fabregat-Traver, Paolo Bientinesi:
Knowledge-Based Automatic Generation of Partitioned Matrix Expressions. CoRR abs/1410.0567 (2014) - 2013
- [j15]Paolo Bientinesi, John A. Gunnels, Margaret E. Myers, Enrique S. Quintana-Ortí, Tyler Rhodes, Robert A. van de Geijn, Field G. Van Zee:
Deriving dense linear algebra libraries. Formal Aspects Comput. 25(6): 933-945 (2013) - [j14]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) - [j13]Lukas Krämer, Edoardo Di Napoli, Martin Galgon, Bruno Lang, Paolo Bientinesi:
Dissecting the FEAST algorithm for generalized eigenproblems. J. Comput. Appl. Math. 244: 1-9 (2013) - [j12]Matthias Petschow, Elmar Peise, Paolo Bientinesi:
High-Performance Solvers for Dense Hermitian Eigenproblems. SIAM J. Sci. Comput. 35(1) (2013) - [c15]Lucas Beyer, Paolo Bientinesi:
GWAS on GPUs: Streaming Data from HDD for Sustained Performance. Euro-Par 2013: 788-799 - [c14]Elmar Peise, Diego Fabregat-Traver, Yurii S. Aulchenko, Paolo Bientinesi:
Algorithms for large-scale whole genome association analysis. EuroMPI 2013: 229-234 - [i16]Lucas Beyer, Paolo Bientinesi:
Streaming Data from HDD to GPUs for Sustained Peak Performance. CoRR abs/1302.4332 (2013) - [i15]Matthias Petschow, Enrique S. Quintana-Ortí, Paolo Bientinesi:
Improved Accuracy and Parallelism for MRRR-based Eigensolvers -- A Mixed Precision Approach. CoRR abs/1304.1864 (2013) - [i14]Elmar Peise, Diego Fabregat-Traver, Yurii S. Aulchenko, Paolo Bientinesi:
Algorithms for Large-scale Whole Genome Association Analysis. CoRR abs/1304.2272 (2013) - [i13]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
- [j11]José Ignacio Aliaga, Paolo Bientinesi, Davor Davidovic, Edoardo Di Napoli, Francisco D. Igual, Enrique S. Quintana-Ortí:
Solving dense generalized eigenproblems on multi-threaded architectures. Appl. Math. Comput. 218(22): 11279-11289 (2012) - [j10]Edoardo Di Napoli, Stefan Blügel, Paolo Bientinesi:
Correlations in sequences of generalized eigenproblems arising in Density Functional Theory. Comput. Phys. Commun. 183(8): 1674-1682 (2012) - [j9]Roman Iakymchuk, Paolo Bientinesi:
Modeling performance through memory-stalls. SIGMETRICS Perform. Evaluation Rev. 40(2): 86-91 (2012) - [c13]Elmar Peise, Paolo Bientinesi:
Performance Modeling for Dense Linear Algebra. SC Companion 2012: 406-416 - [c12]Diego Fabregat-Traver, Paolo Bientinesi:
A Domain-Specific Compiler for Linear Algebra Operations. VECPAR 2012: 346-361 - [i12]Lukas Krämer, Edoardo Di Napoli, Martin Galgon, Bruno Lang, Paolo Bientinesi:
Dissecting the FEAST algorithm for generalized Eigenproblems. CoRR abs/1204.1726 (2012) - [i11]Matthias Petschow, Elmar Peise, Paolo Bientinesi:
High-Performance Solvers for Dense Hermitian Eigenproblems. CoRR abs/1205.2107 (2012) - [i10]Diego Fabregat-Traver, Paolo Bientinesi:
A Domain-Specific Compiler for Linear Algebra Operations. CoRR abs/1205.5975 (2012) - [i9]Diego Fabregat-Traver, Yurii S. Aulchenko, Paolo Bientinesi:
High-throughput Genome-wide Association Analysis for Single and Multiple Phenotypes. CoRR abs/1207.2169 (2012) - [i8]Elmar Peise, Paolo Bientinesi:
Performance Modeling for Dense Linear Algebra. CoRR abs/1209.2364 (2012) - [i7]Diego Fabregat-Traver, Yurii S. Aulchenko, Paolo Bientinesi:
Solving Sequences of Generalized Least-Squares Problems on Multi-threaded Architectures. CoRR abs/1210.7325 (2012) - [i6]Diego Fabregat-Traver, Paolo Bientinesi:
Computing Petaflops over Terabytes of Data: The Case of Genome-Wide Association Studies. CoRR abs/1210.7683 (2012) - [i5]Diego Fabregat-Traver, Paolo Bientinesi:
Application-tailored Linear Algebra Algorithms: A search-based Approach. CoRR abs/1211.5904 (2012) - 2011
- [j8]Paolo Bientinesi, Francisco D. Igual, Daniel Kressner, Matthias Petschow, Enrique S. Quintana-Ortí:
Condensed forms for the symmetric eigenvalue problem on multi-threaded architectures. Concurr. Comput. Pract. Exp. 23(7): 694-707 (2011) - [j7]Matthias Petschow, Paolo Bientinesi:
MR3-SMP: A symmetric tridiagonal eigensolver for multi-core architectures. Parallel Comput. 37(12): 795-805 (2011) - [j6]