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Umeå universitet
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Huvudmenyn dold.

Paolo Bientinesi

Jag är professor i datavetenskap med inriktning mot högprestandaberäkningar. 

Vetenskaplig meritering: Docent
0000-0002-4972-7097

Kontakt

E-post
paolo.bientinesi@umu.se
Telefon
072-085 61 80

Verksam vid

Anknytning
Professor vid Institutionen för datavetenskap
Plats
MIT-huset, Umeå universitet, UMIT, MIT.A.221 Umeå universitet, 901 87 Umeå
Anknytning
Anknuten som professor till Högpresterande beräkningscentrum Norr (HPC2N) Roll: Föreståndare
Plats
MIT huset, Campustorget 5, 2 tr Umeå universitet, 901 87 Umeå

Mina forskningsintressen berör numerisk linjär algebra, tensoroperationer, prestandamodellering och förutsägelse, datormusik och automatisk generering av algoritmer och kod.

Jag är särskilt intresserad av tvärvetenskaplig forskning, till exempel inom materialvetenskap, molekylär dynamik, såväl som beräkningskemi, biologi och fysik.

Den röda tråden i min forskning är utnyttjande av domänspecifik, problemspecifik och arkitekturspecifik kunskap för utveckling av högpresterande algoritmer.

Mer information om min forskning, CV och publikationer

 

High-quality and reproducible automatic drum transcription from crowdsourced data
Signals, MDPI 2023, Vol. 4, (4) : 768-787
Zehren, Mickaël; Alunno, Marco; Bientinesi, Paolo
Work-Stealing Prefix Scan: Addressing Load Imbalance in Large-Scale Image Registration
IEEE Transactions on Parallel and Distributed Systems, IEEE Computer Society 2022, Vol. 33, (3) : 523-535
Copik, Marcin; Grosser, Tobias; Hoefler, Torsten; et al.
Editorial: High-performance tensor computations in scientific computing and data science
Frontiers in Applied Mathematics and Statistics, Frontiers Media S.A. 2022, Vol. 8
Di Napoli, Edoardo; Bientinesi, Paolo; Li, Jiajia; et al.
FLOPs as a discriminant for dense linear algebra algorithms
ICPP '22: proceedings of the 51st international conference on parallel processing
López, Francisco; Karlsson, Lars; Bientinesi, Paolo
The linear algebra mapping problem: Current state of linear algebra languages and libraries
ACM Transactions on Mathematical Software, ACM Digital Library 2022, Vol. 48, (3)
Psarras, Christos; Barthels, Henrik; Bientinesi, Paolo
Algorithm 1026: Concurrent Alternating Least Squares for Multiple Simultaneous Canonical Polyadic Decompositions
ACM Transactions on Mathematical Software, ACM Digital Library 2022, Vol. 48, (3)
Psarras, Christos; Karlsson, Lars; Bro, Rasmus; et al.
Accelerating Jackknife Resampling for the Canonical Polyadic Decomposition
Frontiers in Applied Mathematics and Statistics, Vol. 8
Psarras, Christos; Karlsson, Lars; Bro, Rasmus; et al.
Benchmarking the Linear Algebra Awareness of TensorFlow and PyTorch
Proceedings: 2022 IEEE 36th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2022, IEEE 2022 : 924-933
Sankaran, Aravind; Alashti, Navid Akbari; Psarras, Christos; et al.
A test for FLOPs as a discriminant for linear algebra algorithms
2022 IEEE 34th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), IEEE 2022 : 221-230
Sankaran, Aravind; Bientinesi, Paolo
Automatic detection of cue points for the emulation of DJ mixing
Computer music journal, MIT Press 2022, Vol. 46, (3) : 67-82
Zehren, Mickaël; Alunno, Marco; Bientinesi, Paolo
Linnea: Automatic Generation of Efficient Linear Algebra Programs
ACM Transactions on Mathematical Software, ACM Digital Library 2021, Vol. 47, (3)
Barthels, Henrik; Psarras, Christos; Bientinesi, Paolo
Rational spectral filters with optimal convergence rate
SIAM Journal on Scientific Computing, Society for Industrial and Applied Mathematics Publications 2021, Vol. 43, (4) : A2660-A2684
Kollnig, Konrad; Bientinesi, Paolo; Di Napoli, Edoardo A.
Performance Comparison for Scientific Computations on the Edge via Relative Performance
IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW): 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), IEEE 2021 : 887-895
Sankaran, Aravind; Bientinesi, Paolo
ADTOF: A large dataset of non-synthetic music for automatic drum transcription
Proceedings of the 22nd International Society for Music Information Retrieval Conference : 818-824
Zehren, Mickaël; Alunno, Marco; Bientinesi, Paolo
Automatic Generation of Efficient Linear Algebra Programs
PASC '20: Proceedings of the Platform for Advanced Scientific Computing Conference
Barthels, Henrik; Psarras, Christos; Bientinesi, Paolo
Accelerating Deep Learning Inference in Constrained Embedded Devices Using Hardware Loops and a Dot Product Unit
IEEE Access, IEEE 2020, Vol. 8 : 165913-165926
Vreča, Jure; Sturm, Karl J. X.; Gungl, Ernest; et al.
Visa publikationer i DiVA

Forskargrupper

Forskningsledare
Högpresterande och automatisk databehandling